Index (Evolver 2.0-SNAPSHOT API)

A B C D E F G H I K L M N O P R S T U V W Y Z
All Classes and Interfaces|All Packages|Constant Field Values|Serialized Form

A

addConditionalParameter(boolean, Parameter<?>) - Method in class org.uma.evolver.parameter.ConditionalParameterManager: Adds a conditional parameter that becomes active when the main parameter equals the specified boolean value.
addConditionalParameter(int, Parameter<?>) - Method in class org.uma.evolver.parameter.ConditionalParameterManager: Adds a conditional parameter that becomes active when the main parameter equals the specified integer value.
addConditionalParameter(Boolean, Parameter<?>) - Method in class org.uma.evolver.parameter.Parameter: Adds a specific sub-parameter that depends on a boolean value.
addConditionalParameter(String, Parameter<?>) - Method in class org.uma.evolver.parameter.ConditionalParameterManager: Adds a conditional parameter that becomes active when the main parameter equals the specified string value.
addConditionalParameter(String, Parameter<?>) - Method in class org.uma.evolver.parameter.Parameter: Adds a specific sub-parameter that depends on a string value.
addConditionalParameter(Predicate<T>, Parameter<?>, String) - Method in class org.uma.evolver.parameter.ConditionalParameterManager: Adds a conditional parameter with a custom predicate condition.
addGlobalSubParameter(Parameter<?>) - Method in class org.uma.evolver.parameter.Parameter: Adds a global sub-parameter to this parameter.
addNonConfigurableSubParameter(String, Object) - Method in class org.uma.evolver.parameter.Parameter: Adds a non-configurable sub-parameter to this parameter.
addTopLevelParameter(Parameter<?>) - Method in class org.uma.evolver.parameter.ParameterSpace: Adds a parameter to the list of top-level parameters.
AGGREGATION_FUNCTION - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADCommonParameterSpace
aggregationFunction - Variable in class org.uma.evolver.algorithm.base.moead.BaseMOEAD: Aggregation function for scalarizing objectives.
AggregationFunctionParameter - Class in org.uma.evolver.parameter.catalogue: A categorical parameter representing different aggregation functions used in decomposition-based multi-objective optimization algorithms like MOEA/D.
AggregationFunctionParameter(String, List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.AggregationFunctionParameter: Creates a new AggregationFunctionParameter with the specified name and aggregation function options.
AggregationFunctionParameter(List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.AggregationFunctionParameter: Creates a new AggregationFunctionParameter with the specified aggregation function options.
ALGORITHM_RESULT - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADCommonParameterSpace
ALGORITHM_RESULT - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
ALGORITHM_RESULT - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIICommonParameterSpace
ALGORITHM_RESULT - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEACommonParameterSpace
ARCHIVE_TYPE - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIICommonParameterSpace
ARCHIVE_TYPE - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEACommonParameterSpace
ARITHMETIC - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADDoubleParameterSpace
ARITHMETIC - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIDoubleParameterSpace
AsyncNSGAIIOptimizingNSGAIIForBenchmarkWFG - Class in org.uma.evolver.example.meta: Class for running NSGA-II as meta-optimizer to configure DoubleNSGAII using the WFG problems as training set.
AsyncNSGAIIOptimizingNSGAIIForBenchmarkWFG() - Constructor for class org.uma.evolver.example.meta.AsyncNSGAIIOptimizingNSGAIIForBenchmarkWFG
AutoNSGAIIIraceHV - Class in org.uma.evolver.util.irace: A utility class for running NSGA-II with irace for automatic algorithm configuration.
AutoNSGAIIIraceHV() - Constructor for class org.uma.evolver.util.irace.AutoNSGAIIIraceHV

B

BaseLevelAlgorithm<S> - Interface in org.uma.evolver.algorithm.base: Interface representing a configurable evolutionary algorithm.
BaseMOEAD<S> - Class in org.uma.evolver.algorithm.base.moead: Abstract base class for configurable implementations of the MOEA/D (Multi-Objective Evolutionary Algorithm based on Decomposition) algorithm.
BaseMOEAD(int, String, ParameterSpace) - Constructor for class org.uma.evolver.algorithm.base.moead.BaseMOEAD: Constructs a new BaseMOEAD instance with the specified population size, weight vector directory, and parameter space.
BaseMOEAD(Problem<S>, int, int, String, ParameterSpace) - Constructor for class org.uma.evolver.algorithm.base.moead.BaseMOEAD: Constructs a fully configured BaseMOEAD instance ready for execution.
BaseMOPSO - Class in org.uma.evolver.algorithm.base.mopso: Base class for Multi-Objective Particle Swarm Optimization (MOPSO) algorithms.
BaseMOPSO(int, ParameterSpace) - Constructor for class org.uma.evolver.algorithm.base.mopso.BaseMOPSO: Constructs a new BaseMOPSO instance with the specified leader archive size and parameter space.
BaseMOPSO(DoubleProblem, int, int, ParameterSpace) - Constructor for class org.uma.evolver.algorithm.base.mopso.BaseMOPSO: Constructs a fully configured BaseMOPSO instance ready for execution.
BaseNSGAII<S> - Class in org.uma.evolver.algorithm.base.nsgaii: Abstract base class for configurable NSGA-II (Non-dominated Sorting Genetic Algorithm II) implementations.
BaseNSGAII(int, ParameterSpace) - Constructor for class org.uma.evolver.algorithm.base.nsgaii.BaseNSGAII: Constructs a new BaseNSGAII instance with the specified population size and parameter space.
BaseNSGAII(Problem<S>, int, int, ParameterSpace) - Constructor for class org.uma.evolver.algorithm.base.nsgaii.BaseNSGAII: Constructs a fully configured BaseNSGAII instance ready for execution.
BaseRDEMOEA<S> - Class in org.uma.evolver.algorithm.base.rdsmoea: Abstract base class for configurable NSGA-II algorithm implementations for evolutionary algorithms.
BaseRDEMOEA(int, ParameterSpace) - Constructor for class org.uma.evolver.algorithm.base.rdsmoea.BaseRDEMOEA: Constructs an AbstractNSGAII with the given population size and parameter space.
BaseRDEMOEA(Problem<S>, int, int, ParameterSpace) - Constructor for class org.uma.evolver.algorithm.base.rdsmoea.BaseRDEMOEA: Constructs an AbstractNSGAII with the given problem, population size, maximum number of evaluations, and parameter space.
BaseSMSEMOA<S> - Class in org.uma.evolver.algorithm.base.smsemoa: Abstract base class for configurable SMS-EMOA (S-Metric Selection Evolutionary Multi-Objective Algorithm) implementations for evolutionary algorithms.
BaseSMSEMOA(int, ParameterSpace) - Constructor for class org.uma.evolver.algorithm.base.smsemoa.BaseSMSEMOA: Constructs an AbstractNSGAII with the given population size and parameter space.
BaseSMSEMOA(Problem<S>, int, int, ParameterSpace) - Constructor for class org.uma.evolver.algorithm.base.smsemoa.BaseSMSEMOA: Constructs an AbstractNSGAII with the given problem, population size, maximum number of evaluations, and parameter space.
BinaryCrossoverParameter - Class in org.uma.evolver.parameter.catalogue.crossoverparameter: Parameter class representing the configuration and factory for crossover operators for BinarySolution in evolutionary algorithms.
BinaryCrossoverParameter(String, List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.crossoverparameter.BinaryCrossoverParameter: Constructs a new BinaryCrossoverParameter with the specified list of crossover operator names.
BinaryCrossoverParameter(List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.crossoverparameter.BinaryCrossoverParameter: Constructs a new BinaryCrossoverParameter with the specified list of crossover operator names.
BinaryMOEAD - Class in org.uma.evolver.algorithm.base.moead: Configurable implementation of the MOEA/D algorithm for binary-based problems.
BinaryMOEAD(int, String, ParameterSpace) - Constructor for class org.uma.evolver.algorithm.base.moead.BinaryMOEAD: Constructs a new BinaryMOEAD instance with the specified population size, weight vector files directory, and parameter space.
BinaryMOEAD(Problem<BinarySolution>, int, int, String, ParameterSpace) - Constructor for class org.uma.evolver.algorithm.base.moead.BinaryMOEAD: Constructs a fully configured BinaryMOEAD instance ready for execution.
BinaryMutationParameter - Class in org.uma.evolver.parameter.catalogue.mutationparameter: A parameter class for configuring binary mutation operators in evolutionary algorithms.
BinaryMutationParameter(String, List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.mutationparameter.BinaryMutationParameter: Constructs a new MutationBinaryParameter with the specified list of mutation operator names.
BinaryMutationParameter(List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.mutationparameter.BinaryMutationParameter: Constructs a new MutationBinaryParameter with the specified list of mutation operator names.
BinaryNSGAII - Class in org.uma.evolver.algorithm.base.nsgaii: A configurable implementation of the Non-dominated Sorting Genetic Algorithm II (NSGA-II) specifically designed for binary-encoded optimization problems.
BinaryNSGAII(int, ParameterSpace) - Constructor for class org.uma.evolver.algorithm.base.nsgaii.BinaryNSGAII: Constructs a new instance of BinaryNSGAII with the specified population size and parameter space.
BinaryNSGAII(Problem<BinarySolution>, int, int, ParameterSpace) - Constructor for class org.uma.evolver.algorithm.base.nsgaii.BinaryNSGAII: Constructs a fully configured BinaryNSGAII instance ready for execution.
BinaryParameterFactory - Class in org.uma.evolver.parameter.factory: Factory class for creating and configuring categorical parameters specific to evolutionary algorithms that operate on BinarySolution individuals.
BinaryParameterFactory() - Constructor for class org.uma.evolver.parameter.factory.BinaryParameterFactory
BinaryVariationParameter - Class in org.uma.evolver.parameter.catalogue.variationparameter: A parameter class for configuring variation operators specifically designed for binary solutions.
BinaryVariationParameter(String, List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.variationparameter.BinaryVariationParameter: Constructs a new VariationBinaryParameter with the specified list of variation strategy names.
BinaryVariationParameter(List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.variationparameter.BinaryVariationParameter: Constructs a new VariationBinaryParameter with the specified list of variation strategy names.
BIT_FLIP - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADBinaryParameterSpace
BIT_FLIP_MUTATION - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIBinaryParameterSpace
BLX_ALPHA - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADDoubleParameterSpace
BLX_ALPHA - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIDoubleParameterSpace
BLX_ALPHA - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEADoubleParameterSpace
BLX_ALPHA_BETA - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADDoubleParameterSpace
BLX_ALPHA_BETA - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIDoubleParameterSpace
BLX_ALPHA_BETA_CROSSOVER_ALPHA - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADDoubleParameterSpace
BLX_ALPHA_BETA_CROSSOVER_ALPHA - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIDoubleParameterSpace
BLX_ALPHA_BETA_CROSSOVER_BETA - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADDoubleParameterSpace
BLX_ALPHA_BETA_CROSSOVER_BETA - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIDoubleParameterSpace
BLX_ALPHA_CROSSOVER_ALPHA - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADDoubleParameterSpace
BLX_ALPHA_CROSSOVER_ALPHA - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIDoubleParameterSpace
BLX_ALPHA_CROSSOVER_ALPHA_VALUE - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEADoubleParameterSpace
BooleanParameter - Class in org.uma.evolver.parameter.type: A parameter representing a boolean value.
BooleanParameter(String) - Constructor for class org.uma.evolver.parameter.type.BooleanParameter: Constructs a new BooleanParameter.
BOUNDS - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADDoubleParameterSpace
build() - Method in interface org.uma.evolver.algorithm.base.BaseLevelAlgorithm: Builds and returns a configured Algorithm instance.
build() - Method in class org.uma.evolver.algorithm.base.moead.BaseMOEAD: Builds and configures the MOEA/D algorithm based on the current parameter space.
build() - Method in class org.uma.evolver.algorithm.base.mopso.BaseMOPSO: Builds and configures the MOPSO algorithm based on the current parameter space.
build() - Method in class org.uma.evolver.algorithm.base.nsgaii.BaseNSGAII: Builds and configures the NSGA-II algorithm based on the current parameter space.
build() - Method in class org.uma.evolver.algorithm.base.rdsmoea.BaseRDEMOEA: Builds and returns a configured EvolutionaryAlgorithm instance using the current parameter space and problem settings.
build() - Method in class org.uma.evolver.algorithm.base.smsemoa.BaseSMSEMOA: Builds and returns a configured EvolutionaryAlgorithm instance using the current parameter space and problem settings.
build() - Method in class org.uma.evolver.algorithm.meta.MetaAsyncNSGAIIBuilder: Builds and configures an asynchronous multi-threaded NSGA-II instance.
build() - Method in class org.uma.evolver.algorithm.meta.MetaNSGAIIBuilder: Builds and configures an NSGA-II instance with the specified parameters.
build() - Method in class org.uma.evolver.algorithm.meta.MetaSMPSOBuilder: Builds and configures an SMPSO instance with the specified parameters.
build(String, SolutionsCreation<DoubleSolution>, Evaluation<DoubleSolution>, Termination, VelocityInitialization, LocalBestInitialization, GlobalBestInitialization, InertiaWeightComputingStrategy, VelocityUpdate, PositionUpdate, Perturbation, GlobalBestUpdate, LocalBestUpdate, GlobalBestSelection, BoundedArchive<DoubleSolution>, Archive<DoubleSolution>) - Method in class org.uma.evolver.algorithm.base.ParticleSwarmOptimizationBuilder: Builds an instance of ParticleSwarmOptimizationAlgorithm with the specified components.
build(String, SolutionsCreation<S>, Evaluation<S>, Termination, Selection<S>, Variation<S>, Replacement<S>, Archive<S>) - Method in class org.uma.evolver.algorithm.base.EvolutionaryAlgorithmBuilder: Builds an instance of EvolutionaryAlgorithm with the specified components.

C

C1_MAX - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
C1_MIN - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
C2_MAX - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
C2_MIN - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
CategoricalIntegerParameter - Class in org.uma.evolver.parameter.type: A parameter representing a categorical value selected from a predefined list of valid integers.
CategoricalIntegerParameter(String, List<Integer>) - Constructor for class org.uma.evolver.parameter.type.CategoricalIntegerParameter: Constructs a new CategoricalIntegerParameter.
CategoricalParameter - Class in org.uma.evolver.parameter.type: A parameter representing a categorical value selected from a predefined list of valid values.
CategoricalParameter(String, List<String>) - Constructor for class org.uma.evolver.parameter.type.CategoricalParameter: Constructs a new CategoricalParameter.
CategoricalParameterProcessor - Class in org.uma.evolver.parameter.yaml.processors: Processes categorical parameters from YAML configuration.
CategoricalParameterProcessor(ParameterFactory<?>) - Constructor for class org.uma.evolver.parameter.yaml.processors.CategoricalParameterProcessor
compute(double[][]) - Method in class org.uma.evolver.util.EvaluationsQualityIndicator
compute(double[][]) - Method in class org.uma.evolver.util.HypervolumeMinus
condition() - Method in class org.uma.evolver.parameter.ConditionalParameter: Returns the predicate condition associated with this conditional parameter.
ConditionalParameter<T> - Class in org.uma.evolver.parameter: Represents a parameter that becomes active only when a specified condition is satisfied by the value of another parameter in a multi-objective metaheuristic parameter space.
ConditionalParameter(Predicate<T>, Parameter<?>, String) - Constructor for class org.uma.evolver.parameter.ConditionalParameter: Constructs a new ConditionalParameter with the specified condition, parameter, and description.
ConditionalParameterManager<T> - Class in org.uma.evolver.parameter: Manages a collection of ConditionalParameter objects associated with a main parameter in a multi-objective metaheuristic parameter space.
ConditionalParameterManager() - Constructor for class org.uma.evolver.parameter.ConditionalParameterManager
conditionalParameters() - Method in class org.uma.evolver.parameter.ConditionalParameterManager: Returns an unmodifiable view of all managed conditional parameters.
conditionalParameters() - Method in class org.uma.evolver.parameter.Parameter: Returns the list of specific sub-parameters associated with this parameter.
Configuration Parameters - Search tag in class org.uma.evolver.algorithm.base.moead.BinaryMOEAD: Section
Configuration Parameters - Search tag in class org.uma.evolver.algorithm.base.moead.DoubleMOEAD: Section
Configuration Parameters - Search tag in class org.uma.evolver.algorithm.base.moead.PermutationMOEAD: Section
CONSTANT_VALUE - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
CONSTRAINED_VELOCITY_UPDATE - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
CR - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADDoubleParameterSpace
CREATE_INITIAL_SOLUTIONS - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADCommonParameterSpace
CREATE_INITIAL_SOLUTIONS - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIICommonParameterSpace
CREATE_INITIAL_SOLUTIONS - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEACommonParameterSpace
createEvaluation() - Method in class org.uma.evolver.algorithm.base.mopso.BaseMOPSO: Creates the evaluation component for the algorithm.
createEvaluation(Archive<S>) - Method in class org.uma.evolver.algorithm.base.moead.BaseMOEAD: Creates the evaluation component for the algorithm.
createEvaluation(Archive<S>) - Method in class org.uma.evolver.algorithm.base.nsgaii.BaseNSGAII: Creates the evaluation component for the algorithm.
createEvaluation(Archive<S>) - Method in class org.uma.evolver.algorithm.base.rdsmoea.BaseRDEMOEA: Creates the evaluation component for the algorithm.
createEvaluation(Archive<S>) - Method in class org.uma.evolver.algorithm.base.smsemoa.BaseSMSEMOA: Creates the evaluation component for the algorithm.
createExternalArchive() - Method in class org.uma.evolver.algorithm.base.mopso.BaseMOPSO: Creates and configures the external archive based on the parameter space settings.
createExternalArchive() - Method in class org.uma.evolver.algorithm.base.nsgaii.BaseNSGAII: Creates and configures the external archive if required by the parameter space.
createExternalArchive() - Method in class org.uma.evolver.algorithm.base.rdsmoea.BaseRDEMOEA: Creates and configures the external archive if required by the parameter space.
createExternalArchive() - Method in class org.uma.evolver.algorithm.base.smsemoa.BaseSMSEMOA: Creates and configures the external archive if required by the parameter space.
createGlobalBestInitialization() - Method in class org.uma.evolver.algorithm.base.mopso.BaseMOPSO: Creates the strategy for initializing global best solutions.
createGlobalBestSelection() - Method in class org.uma.evolver.algorithm.base.mopso.BaseMOPSO: Creates the strategy for selecting the global best solution.
createGlobalBestUpdate() - Method in class org.uma.evolver.algorithm.base.mopso.BaseMOPSO: Creates the strategy for updating the global best solution.
createInertiaWeightStrategy() - Method in class org.uma.evolver.algorithm.base.mopso.BaseMOPSO: Creates the strategy for computing inertia weight during the search.
createInitialSolutions() - Method in class org.uma.evolver.algorithm.base.moead.BaseMOEAD: Creates the component responsible for generating the initial population of solutions.
createInitialSolutions() - Method in class org.uma.evolver.algorithm.base.nsgaii.BaseNSGAII: Creates the initial solutions creation strategy using the configured parameter.
createInitialSolutions() - Method in class org.uma.evolver.algorithm.base.rdsmoea.BaseRDEMOEA: Creates the initial solutions creation strategy using the configured parameter.
createInitialSolutions() - Method in class org.uma.evolver.algorithm.base.smsemoa.BaseSMSEMOA: Creates the initial solutions creation strategy using the configured parameter.
CreateInitialSolutionsBinaryParameter - Class in org.uma.evolver.parameter.catalogue.createinitialsolutionsparameter: A parameter for creating initial binary solutions in evolutionary algorithms.
CreateInitialSolutionsBinaryParameter(String, List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.createinitialsolutionsparameter.CreateInitialSolutionsBinaryParameter: Creates a new CreateInitialSolutionsBinaryParameter with the specified name and valid values.
CreateInitialSolutionsBinaryParameter(List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.createinitialsolutionsparameter.CreateInitialSolutionsBinaryParameter: Creates a new CreateInitialSolutionsBinaryParameter with the specified valid values.
createInitialSolutionsCreation() - Method in class org.uma.evolver.algorithm.base.mopso.BaseMOPSO: Creates the component responsible for generating the initial population of solutions.
CreateInitialSolutionsDoubleParameter - Class in org.uma.evolver.parameter.catalogue.createinitialsolutionsparameter: A parameter for creating initial double solutions in evolutionary algorithms.
CreateInitialSolutionsDoubleParameter(String, List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.createinitialsolutionsparameter.CreateInitialSolutionsDoubleParameter: Creates a new CreateInitialSolutionsDoubleParameter with the specified name and valid values.
CreateInitialSolutionsDoubleParameter(List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.createinitialsolutionsparameter.CreateInitialSolutionsDoubleParameter: Creates a new CreateInitialSolutionsDoubleParameter with the specified valid values.
CreateInitialSolutionsParameter<S> - Class in org.uma.evolver.parameter.catalogue.createinitialsolutionsparameter: An abstract categorical parameter for creating initial solutions in evolutionary algorithms.
CreateInitialSolutionsParameter(String, List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.createinitialsolutionsparameter.CreateInitialSolutionsParameter: Creates a new CreateInitialSolutionsParameter with the specified name and valid values.
CreateInitialSolutionsParameter(List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.createinitialsolutionsparameter.CreateInitialSolutionsParameter: Creates a new CreateInitialSolutionsParameter with the specified valid values.
CreateInitialSolutionsPermutationParameter - Class in org.uma.evolver.parameter.catalogue.createinitialsolutionsparameter: A parameter for creating initial permutation solutions in evolutionary algorithms.
CreateInitialSolutionsPermutationParameter(String, List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.createinitialsolutionsparameter.CreateInitialSolutionsPermutationParameter: Creates a new CreateInitialSolutionsPermutationParameter with the specified name and valid values.
CreateInitialSolutionsPermutationParameter(List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.createinitialsolutionsparameter.CreateInitialSolutionsPermutationParameter: Creates a new CreateInitialSolutionsPermutationParameter with the specified valid values.
createInstance() - Method in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADBinaryParameterSpace
createInstance() - Method in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADDoubleParameterSpace
createInstance() - Method in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADPermutationParameterSpace
createInstance() - Method in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
createInstance() - Method in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIBinaryParameterSpace
createInstance() - Method in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIDoubleParameterSpace
createInstance() - Method in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIPermutationParameterSpace
createInstance() - Method in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEADoubleParameterSpace
createInstance() - Method in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEAPermutationParameterSpace
createInstance() - Method in class org.uma.evolver.parameter.ParameterSpace: Creates and configures a new instance of this parameter space.
createInstance() - Method in class org.uma.evolver.parameter.yaml.YAMLParameterSpace
createInstance(Problem<BinarySolution>, int) - Method in class org.uma.evolver.algorithm.base.moead.BinaryMOEAD: Creates a new instance of BinaryMOEAD for the given problem and maximum number of evaluations.
createInstance(Problem<BinarySolution>, int) - Method in class org.uma.evolver.algorithm.base.nsgaii.BinaryNSGAII: Creates and returns a new instance of BinaryNSGAII configured for the specified problem.
createInstance(Problem<DoubleSolution>, int) - Method in class org.uma.evolver.algorithm.base.moead.DoubleMOEAD: Creates a new instance of DoubleMOEAD for the given problem and maximum number of evaluations.
createInstance(Problem<DoubleSolution>, int) - Method in class org.uma.evolver.algorithm.base.mopso.BaseMOPSO: Creates a new instance of BaseMOPSO configured for the specified problem and evaluation limit.
createInstance(Problem<DoubleSolution>, int) - Method in class org.uma.evolver.algorithm.base.nsgaii.DoubleNSGAII: Creates and returns a new instance of DoubleNSGAII configured for the specified problem.
createInstance(Problem<DoubleSolution>, int) - Method in class org.uma.evolver.algorithm.base.rdsmoea.DoubleRDEMOEA: Creates a new instance of NSGAIIDouble for the given problem and maximum number of evaluations.
createInstance(Problem<DoubleSolution>, int) - Method in class org.uma.evolver.algorithm.base.smsemoa.DoubleSMSEMOA: Creates a new instance of DoubleSMSEMOA for the given problem and maximum number of evaluations.
createInstance(Problem<PermutationSolution<Integer>>, int) - Method in class org.uma.evolver.algorithm.base.moead.PermutationMOEAD: Creates a new instance of PermutationMOEAD for the given problem and maximum number of evaluations.
createInstance(Problem<PermutationSolution<Integer>>, int) - Method in class org.uma.evolver.algorithm.base.nsgaii.PermutationNSGAII: Creates and returns a new instance of PermutationNSGAII configured for the specified problem.
createInstance(Problem<PermutationSolution<Integer>>, int) - Method in class org.uma.evolver.algorithm.base.rdsmoea.PermutationRDEMOEA: Creates a new instance of NSGAIIPermutation for the given problem and maximum number of evaluations.
createInstance(Problem<S>, int) - Method in interface org.uma.evolver.algorithm.base.BaseLevelAlgorithm: Creates a new instance of the algorithm for the given problem and maximum number of evaluations.
createLocalBestInitialization() - Method in class org.uma.evolver.algorithm.base.mopso.BaseMOPSO: Creates the strategy for initializing local best solutions.
createLocalBestUpdate() - Method in class org.uma.evolver.algorithm.base.mopso.BaseMOPSO: Creates the strategy for updating local best solutions.
createParameter(String, List<String>) - Method in class org.uma.evolver.parameter.factory.BinaryParameterFactory: Creates and returns a specific CategoricalParameter instance based on the provided parameter name.
createParameter(String, List<String>) - Method in class org.uma.evolver.parameter.factory.DoubleParameterFactory: Creates and returns a specific CategoricalParameter instance based on the provided parameter name.
createParameter(String, List<String>) - Method in class org.uma.evolver.parameter.factory.MOPSOParameterFactory: Creates and returns a specific CategoricalParameter instance based on the provided parameter name.
createParameter(String, List<String>) - Method in interface org.uma.evolver.parameter.factory.ParameterFactory: Creates and returns a specific CategoricalParameter instance based on the provided parameter name.
createParameter(String, List<String>) - Method in class org.uma.evolver.parameter.factory.PermutationParameterFactory: Creates and returns a specific CategoricalParameter instance based on the provided parameter name.
createPerturbation() - Method in class org.uma.evolver.algorithm.base.mopso.BaseMOPSO: Creates the operator for applying perturbations to solutions.
createPositionUpdate() - Method in class org.uma.evolver.algorithm.base.mopso.BaseMOPSO: Creates the operator for updating particle positions.
createReplacement() - Method in class org.uma.evolver.algorithm.base.nsgaii.BaseNSGAII: Creates the replacement operator for the algorithm using ranking and density estimators.
createReplacement() - Method in class org.uma.evolver.algorithm.base.rdsmoea.BaseRDEMOEA: Creates the replacement operator for the algorithm using ranking and density estimators.
createReplacement() - Method in class org.uma.evolver.algorithm.base.smsemoa.BaseSMSEMOA: Creates the replacement operator for the algorithm using ranking and density estimators.
createReplacement(Selection<S>) - Method in class org.uma.evolver.algorithm.base.moead.BaseMOEAD: Creates the replacement operator for the algorithm using ranking and density estimators.
createSelection(Variation<S>) - Method in class org.uma.evolver.algorithm.base.nsgaii.BaseNSGAII: Creates the selection operator for the algorithm using the configured selection parameter.
createSelection(Variation<S>) - Method in class org.uma.evolver.algorithm.base.rdsmoea.BaseRDEMOEA: Creates the selection operator for the algorithm using the configured selection parameter.
createSelection(Variation<S>) - Method in class org.uma.evolver.algorithm.base.smsemoa.BaseSMSEMOA: Creates the selection operator for the algorithm using the configured selection parameter.
createTermination() - Method in class org.uma.evolver.algorithm.base.moead.BaseMOEAD: Creates the termination condition for the algorithm.
createTermination() - Method in class org.uma.evolver.algorithm.base.mopso.BaseMOPSO: Creates the termination condition for the algorithm.
createTermination() - Method in class org.uma.evolver.algorithm.base.nsgaii.BaseNSGAII: Creates the termination condition for the algorithm.
createTermination() - Method in class org.uma.evolver.algorithm.base.rdsmoea.BaseRDEMOEA: Creates the termination condition for the algorithm.
createTermination() - Method in class org.uma.evolver.algorithm.base.smsemoa.BaseSMSEMOA: Creates the termination condition for the algorithm.
createVariation() - Method in class org.uma.evolver.algorithm.base.moead.BaseMOEAD: Creates the variation operator for the algorithm.
createVariation() - Method in class org.uma.evolver.algorithm.base.moead.BinaryMOEAD: Creates and configures the variation operator for binary solutions.
createVariation() - Method in class org.uma.evolver.algorithm.base.moead.DoubleMOEAD: Creates and configures the variation operator for real-coded solutions.
createVariation() - Method in class org.uma.evolver.algorithm.base.moead.PermutationMOEAD: Creates and configures the variation operator for permutation solutions.
createVariation() - Method in class org.uma.evolver.algorithm.base.nsgaii.BaseNSGAII: Creates the variation operator for the algorithm using the configured variation parameter.
createVariation() - Method in class org.uma.evolver.algorithm.base.rdsmoea.BaseRDEMOEA: Creates the variation operator for the algorithm using the configured variation parameter.
createVariation() - Method in class org.uma.evolver.algorithm.base.smsemoa.BaseSMSEMOA: Creates the variation operator for the algorithm using the configured variation parameter.
createVelocityInitialization() - Method in class org.uma.evolver.algorithm.base.mopso.BaseMOPSO: Creates the strategy for initializing particle velocities.
createVelocityUpdate() - Method in class org.uma.evolver.algorithm.base.mopso.BaseMOPSO: Creates the operator for updating particle velocities.
CROSSOVER - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADBinaryParameterSpace
CROSSOVER - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADDoubleParameterSpace
CROSSOVER - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADPermutationParameterSpace
CROSSOVER - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIICommonParameterSpace
CROSSOVER - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEACommonParameterSpace
CROSSOVER_AND_MUTATION_VARIATION - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADBinaryParameterSpace
CROSSOVER_AND_MUTATION_VARIATION - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADDoubleParameterSpace
CROSSOVER_AND_MUTATION_VARIATION - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADPermutationParameterSpace
CROSSOVER_AND_MUTATION_VARIATION - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIICommonParameterSpace
CROSSOVER_AND_MUTATION_VARIATION - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEACommonParameterSpace
CROSSOVER_PROBABILITY - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADBinaryParameterSpace
CROSSOVER_PROBABILITY - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADDoubleParameterSpace
CROSSOVER_PROBABILITY - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADPermutationParameterSpace
CROSSOVER_PROBABILITY - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIBinaryParameterSpace
CROSSOVER_PROBABILITY - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIDoubleParameterSpace
CROSSOVER_PROBABILITY - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIPermutationParameterSpace
CROSSOVER_PROBABILITY - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEADoubleParameterSpace
CROSSOVER_PROBABILITY - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEAPermutationParameterSpace
CROSSOVER_REPAIR_STRATEGY - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADDoubleParameterSpace
CROSSOVER_REPAIR_STRATEGY - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIDoubleParameterSpace
CROSSOVER_REPAIR_STRATEGY - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEADoubleParameterSpace
CrossoverParameter<S> - Class in org.uma.evolver.parameter.catalogue.crossoverparameter: Abstract parameter class representing a configurable crossover operator for evolutionary algorithms.
CrossoverParameter(String, List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.crossoverparameter.CrossoverParameter
CrossoverParameter(List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.crossoverparameter.CrossoverParameter: Constructs a crossover parameter with the given list of available crossover operator names.
CROWDING_DISTANCE - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEACommonParameterSpace
CROWDING_DISTANCE_ARCHIVE - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADCommonParameterSpace
CROWDING_DISTANCE_ARCHIVE - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
CROWDING_DISTANCE_ARCHIVE - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIICommonParameterSpace
CROWDING_DISTANCE_ARCHIVE - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEACommonParameterSpace
CX - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADPermutationParameterSpace
CX - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIPermutationParameterSpace
CX - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEAPermutationParameterSpace

D

decodeParameter(Parameter<?>, double) - Static method in class org.uma.evolver.parameter.ParameterManagement
decodeParametersToString(List<Parameter<?>>, List<Double>) - Static method in class org.uma.evolver.parameter.ParameterManagement: Given a list of parameters and a list of the corresponding encoded parameter values in the range [0.0, 1.0], returns a string where each parameter is encoded as sequence of "--parameterName parameterValue" pairs
decodeParameterToDoubleValues(Parameter<?>, double) - Static method in class org.uma.evolver.parameter.ParameterManagement
DEFAULT - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADCommonParameterSpace
DEFAULT - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADPermutationParameterSpace
DEFAULT - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIDoubleParameterSpace
DEFAULT - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIPermutationParameterSpace
DEFAULT - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEADoubleParameterSpace
DEFAULT - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEAPermutationParameterSpace
DEFAULT_GLOBAL_BEST_INITIALIZATION - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
DEFAULT_GLOBAL_BEST_UPDATE - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
DEFAULT_INITIALIZATION - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
DEFAULT_LOCAL_BEST_INITIALIZATION - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
DEFAULT_LOCAL_BEST_UPDATE - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
DEFAULT_NAME - Static variable in class org.uma.evolver.parameter.catalogue.AggregationFunctionParameter
DEFAULT_NAME - Static variable in class org.uma.evolver.parameter.catalogue.createinitialsolutionsparameter.CreateInitialSolutionsParameter
DEFAULT_NAME - Static variable in class org.uma.evolver.parameter.catalogue.crossoverparameter.CrossoverParameter
DEFAULT_NAME - Static variable in class org.uma.evolver.parameter.catalogue.DensityEstimatorParameter
DEFAULT_NAME - Static variable in class org.uma.evolver.parameter.catalogue.DifferentialEvolutionCrossoverParameter
DEFAULT_NAME - Static variable in class org.uma.evolver.parameter.catalogue.DifferentialEvolutionSelectionParameter
DEFAULT_NAME - Static variable in class org.uma.evolver.parameter.catalogue.GlobalBestInitializationParameter
DEFAULT_NAME - Static variable in class org.uma.evolver.parameter.catalogue.GlobalBestSelectionParameter
DEFAULT_NAME - Static variable in class org.uma.evolver.parameter.catalogue.GlobalBestUpdateParameter
DEFAULT_NAME - Static variable in class org.uma.evolver.parameter.catalogue.InertiaWeightComputingParameter
DEFAULT_NAME - Static variable in class org.uma.evolver.parameter.catalogue.LocalBestInitializationParameter
DEFAULT_NAME - Static variable in class org.uma.evolver.parameter.catalogue.LocalBestUpdateParameter
DEFAULT_NAME - Static variable in class org.uma.evolver.parameter.catalogue.mutationparameter.MutationParameter
DEFAULT_NAME - Static variable in class org.uma.evolver.parameter.catalogue.PerturbationParameter
DEFAULT_NAME - Static variable in class org.uma.evolver.parameter.catalogue.selectionparameter.DoubleSelectionParameter
DEFAULT_NAME - Static variable in class org.uma.evolver.parameter.catalogue.selectionparameter.SelectionParameter
DEFAULT_NAME - Static variable in class org.uma.evolver.parameter.catalogue.variationparameter.VariationParameter
DEFAULT_NAME - Static variable in class org.uma.evolver.parameter.catalogue.VelocityUpdateParameter
DEFAULT_POSITION_UPDATE - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
DEFAULT_STRATEGY - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADBinaryParameterSpace
DEFAULT_STRATEGY - Static variable in class org.uma.evolver.parameter.catalogue.createinitialsolutionsparameter.CreateInitialSolutionsBinaryParameter: The default strategy name for creating initial binary solutions.
DEFAULT_STRATEGY - Static variable in class org.uma.evolver.parameter.catalogue.createinitialsolutionsparameter.CreateInitialSolutionsDoubleParameter: Strategy that creates random double solutions using uniform distribution.
DEFAULT_STRATEGY - Static variable in class org.uma.evolver.parameter.catalogue.createinitialsolutionsparameter.CreateInitialSolutionsPermutationParameter: The default strategy name for creating initial permutation solutions.
DEFAULT_VELOCITY_INITIALIZATION - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
DEFAULT_VELOCITY_UPDATE - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
DENSITY_ESTIMATOR - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEACommonParameterSpace
densityEstimator - Variable in class org.uma.evolver.algorithm.base.nsgaii.BaseNSGAII: The density estimator used for maintaining diversity in the population.
densityEstimator - Variable in class org.uma.evolver.algorithm.base.rdsmoea.BaseRDEMOEA
DensityEstimatorParameter<S> - Class in org.uma.evolver.parameter.catalogue: A categorical parameter representing different density estimator strategies for solutions in multi-objective optimization.
DensityEstimatorParameter(String, List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.DensityEstimatorParameter: Creates a new DensityEstimatorParameter with the specified name and valid density estimator strategies.
DensityEstimatorParameter(List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.DensityEstimatorParameter: Creates a new DensityEstimatorParameter with the specified valid density estimator strategies.
description() - Method in class org.uma.evolver.parameter.ConditionalParameter: Returns the human-readable description of this conditional parameter's condition.
description() - Method in class org.uma.evolver.util.EvaluationsQualityIndicator
DIFFERENTIAL_EVOLUTION_CROSSOVER - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADDoubleParameterSpace
DIFFERENTIAL_EVOLUTION_VARIATION - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADDoubleParameterSpace
DifferentialEvolutionCrossoverParameter - Class in org.uma.evolver.parameter.catalogue: A categorical parameter representing different Differential Evolution (DE) crossover variants.
DifferentialEvolutionCrossoverParameter() - Constructor for class org.uma.evolver.parameter.catalogue.DifferentialEvolutionCrossoverParameter: Creates a new DifferentialEvolutionCrossoverParameter with all standard DE crossover variants.
DifferentialEvolutionCrossoverParameter(String, List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.DifferentialEvolutionCrossoverParameter: Creates a new Diffe rentialEvolutionCrossoverParameter with the specified name and variants.
DifferentialEvolutionCrossoverParameter(List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.DifferentialEvolutionCrossoverParameter: Creates a new DifferentialEvolutionCrossoverParameter with the specified variants.
DifferentialEvolutionSelectionParameter<S> - Class in org.uma.evolver.parameter.catalogue: A categorical parameter representing selection strategies for Differential Evolution (DE) algorithms.
DifferentialEvolutionSelectionParameter(String, List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.DifferentialEvolutionSelectionParameter: Creates a new DifferentialEvolutionSelectionParameter with the specified name and selection strategies.
DifferentialEvolutionSelectionParameter(List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.DifferentialEvolutionSelectionParameter: Creates a new DifferentialEvolutionSelectionParameter with the specified selection strategies.
DISPLACEMENT - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADPermutationParameterSpace
DISPLACEMENT - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIPermutationParameterSpace
DISPLACEMENT - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEAPermutationParameterSpace
DOMINANCE_RANKING - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEACommonParameterSpace
DoubleCrossoverParameter - Class in org.uma.evolver.parameter.catalogue.crossoverparameter: Parameter class representing the configuration and factory for crossover operators for DoubleSolution in evolutionary algorithms.
DoubleCrossoverParameter(String, List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.crossoverparameter.DoubleCrossoverParameter: Constructs a crossover parameter for double solutions with the given list of supported crossover operator names.
DoubleCrossoverParameter(List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.crossoverparameter.DoubleCrossoverParameter: Constructs a crossover parameter for double solutions with the given list of supported crossover operator names.
DoubleMOEAD - Class in org.uma.evolver.algorithm.base.moead: Configurable implementation of the MOEA/D algorithm for real-coded (double) problems.
DoubleMOEAD(int, String, ParameterSpace) - Constructor for class org.uma.evolver.algorithm.base.moead.DoubleMOEAD: Constructs a new DoubleMOEAD instance with the specified population size, weight vector files directory, and parameter space.
DoubleMOEAD(Problem<DoubleSolution>, int, int, String, ParameterSpace) - Constructor for class org.uma.evolver.algorithm.base.moead.DoubleMOEAD: Constructs a fully configured DoubleMOEAD instance ready for execution.
DoubleMutationParameter - Class in org.uma.evolver.parameter.catalogue.mutationparameter: A parameter class for configuring mutation operators specifically designed for double-encoded solutions.
DoubleMutationParameter(String, List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.mutationparameter.DoubleMutationParameter: Constructs a new DoubleMutationParameter with the specified list of mutation operator names.
DoubleMutationParameter(List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.mutationparameter.DoubleMutationParameter: Constructs a new DoubleMutationParameter with the specified list of mutation operator names.
DoubleNSGAII - Class in org.uma.evolver.algorithm.base.nsgaii: A configurable implementation of the Non-dominated Sorting Genetic Algorithm II (NSGA-II) specifically designed for continuous (real-valued) optimization problems.
DoubleNSGAII(int, ParameterSpace) - Constructor for class org.uma.evolver.algorithm.base.nsgaii.DoubleNSGAII: Constructs a new instance of DoubleNSGAII with the specified population size and parameter space.
DoubleNSGAII(Problem<DoubleSolution>, int, int, ParameterSpace) - Constructor for class org.uma.evolver.algorithm.base.nsgaii.DoubleNSGAII: Constructs a fully configured DoubleNSGAII instance ready for execution.
DoubleParameter - Class in org.uma.evolver.parameter.type: A parameter representing a double value constrained within a specified inclusive range.
DoubleParameter(String, double, double) - Constructor for class org.uma.evolver.parameter.type.DoubleParameter: Constructs a DoubleParameter with the given name and range.
DoubleParameterFactory - Class in org.uma.evolver.parameter.factory: Factory class for creating and configuring categorical parameters specific to evolutionary algorithms that operate on DoubleSolution individuals.
DoubleParameterFactory() - Constructor for class org.uma.evolver.parameter.factory.DoubleParameterFactory: Creates a new instance of DoubleParameterFactory with default parameter creators registered.
DoubleParameterProcessor - Class in org.uma.evolver.parameter.yaml.processors: Processes double/real parameters from YAML configuration.
DoubleParameterProcessor() - Constructor for class org.uma.evolver.parameter.yaml.processors.DoubleParameterProcessor: Creates a new DoubleParameterProcessor.
DoubleRDEMOEA - Class in org.uma.evolver.algorithm.base.rdsmoea: Configurable implementation of the NSGA-II algorithm for double-valued (real-coded) problems.
DoubleRDEMOEA(int, ParameterSpace) - Constructor for class org.uma.evolver.algorithm.base.rdsmoea.DoubleRDEMOEA: Constructs an NSGAIIDouble instance with the given population size and a default parameter space.
DoubleRDEMOEA(Problem<DoubleSolution>, int, int, ParameterSpace) - Constructor for class org.uma.evolver.algorithm.base.rdsmoea.DoubleRDEMOEA: Constructs an NSGAIIDouble instance with the given problem, population size, and maximum number of evaluations.
DoubleSelectionParameter - Class in org.uma.evolver.parameter.catalogue.selectionparameter: Specialized selection parameter for double solutions that extends the base CategoricalParameter.
DoubleSelectionParameter() - Constructor for class org.uma.evolver.parameter.catalogue.selectionparameter.DoubleSelectionParameter: Creates a new DoubleSelectionParameter with the default selection strategy.
DoubleSelectionParameter(String, List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.selectionparameter.DoubleSelectionParameter: Creates a new DoubleSelectionParameter with the specified name and selection strategies.
DoubleSelectionParameter(List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.selectionparameter.DoubleSelectionParameter: Creates a new DoubleSelectionParameter with the specified selection strategies.
DoubleSMSEMOA - Class in org.uma.evolver.algorithm.base.smsemoa: Configurable implementation of the SMS-EMOA (S-Metric Selection Evolutionary Multi-Objective Algorithm) for double-valued (real-coded) problems.
DoubleSMSEMOA(int, ParameterSpace) - Constructor for class org.uma.evolver.algorithm.base.smsemoa.DoubleSMSEMOA: Constructs a DoubleSMSEMOA instance with the given population size and parameter space.
DoubleSMSEMOA(Problem<DoubleSolution>, int, int, ParameterSpace) - Constructor for class org.uma.evolver.algorithm.base.smsemoa.DoubleSMSEMOA: Constructs a DoubleSMSEMOA instance with the given problem, population size, maximum number of evaluations, and parameter space.
DoubleVariationParameter - Class in org.uma.evolver.parameter.catalogue.variationparameter: A parameter class for configuring variation operators specifically designed for double-encoded solutions.
DoubleVariationParameter(String, List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.variationparameter.DoubleVariationParameter: Constructs a new VariationDoubleParameter with the specified list of variation strategy names.
DoubleVariationParameter(List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.variationparameter.DoubleVariationParameter: Constructs a new VariationDoubleParameter with the specified list of variation strategy names.
DTLZ3DProblemFamilyInfo - Class in org.uma.evolver.util.problemfamilyinfo
DTLZ3DProblemFamilyInfo() - Constructor for class org.uma.evolver.util.problemfamilyinfo.DTLZ3DProblemFamilyInfo

E

EPSILON_PARAMETER_FOR_NORMALIZATION - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADCommonParameterSpace
evaluate(DoubleSolution) - Method in class org.uma.evolver.metaoptimizationproblem.MetaOptimizationProblem: Evaluates a solution by running the base algorithm with the specified parameter settings and computing the quality indicators.
evaluationBudgetStrategy() - Method in class org.uma.evolver.metaoptimizationproblem.MetaOptimizationProblem: Returns the evaluation strategy being used.
EvaluationBudgetStrategy - Interface in org.uma.evolver.metaoptimizationproblem.evaluationbudgetstrategy: Interface defining the contract for different evaluation budget strategies in meta-optimization problems.
EvaluationsQualityIndicator - Class in org.uma.evolver.util: A specialized quality indicator that tracks and returns the number of evaluations performed by an algorithm.
EvaluationsQualityIndicator() - Constructor for class org.uma.evolver.util.EvaluationsQualityIndicator
evaluationsToOptimize() - Method in class org.uma.evolver.util.problemfamilyinfo.DTLZ3DProblemFamilyInfo
evaluationsToOptimize() - Method in interface org.uma.evolver.util.problemfamilyinfo.ProblemFamilyInfo
evaluationsToOptimize() - Method in class org.uma.evolver.util.problemfamilyinfo.RE3DProblemFamilyInfo
evaluationsToOptimize() - Method in class org.uma.evolver.util.problemfamilyinfo.WFG2DProblemFamilyInfo
evaluationsToOptimize() - Method in class org.uma.evolver.util.problemfamilyinfo.ZDTProblemFamilyInfo
EvolutionaryAlgorithmBuilder<S> - Class in org.uma.evolver.algorithm.base: A builder class for creating instances of EvolutionaryAlgorithm with optional archive support.
EvolutionaryAlgorithmBuilder() - Constructor for class org.uma.evolver.algorithm.base.EvolutionaryAlgorithmBuilder
EXTERNAL_ARCHIVE - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADCommonParameterSpace
EXTERNAL_ARCHIVE - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
EXTERNAL_ARCHIVE - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIICommonParameterSpace
EXTERNAL_ARCHIVE - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEACommonParameterSpace
EXTERNAL_ARCHIVE_TYPE - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
externalArchive - Variable in class org.uma.evolver.algorithm.base.mopso.BaseMOPSO: Optional external archive for storing additional solutions.
externalArchive - Variable in class org.uma.evolver.algorithm.base.nsgaii.BaseNSGAII: Optional external archive for storing non-dominated solutions.
ExternalArchiveParameter<S> - Class in org.uma.evolver.parameter.catalogue: A categorical parameter representing different external archive strategies for multi-objective optimization algorithms.
ExternalArchiveParameter(String, List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.ExternalArchiveParameter: Creates a new ExternalArchiveParameter with the specified parameter name and valid archive types.
ExternalArchiveParameter(List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.ExternalArchiveParameter: Creates a new ExternalArchiveParameter with the default parameter name "externalArchive" and the specified archive types.

F

F - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADDoubleParameterSpace
Features - Search tag in class org.uma.evolver.algorithm.base.moead.BinaryMOEAD: Section
Features - Search tag in class org.uma.evolver.algorithm.base.moead.DoubleMOEAD: Section
Features - Search tag in class org.uma.evolver.algorithm.base.moead.PermutationMOEAD: Section
findConditionalParameter(String) - Method in class org.uma.evolver.parameter.ConditionalParameterManager: Finds a conditional parameter by its name.
findConditionalParameter(String) - Method in class org.uma.evolver.parameter.Parameter: Finds a specific sub-parameter given its name.
findConditionalParameters(String) - Method in class org.uma.evolver.parameter.Parameter: Finds a list of the specific sub-parameters associated with a particular parameter value.
findGlobalSubParameter(String) - Method in class org.uma.evolver.parameter.Parameter: Finds a global sub-parameter given its name.
FixedEvaluationsStrategy - Class in org.uma.evolver.metaoptimizationproblem.evaluationbudgetstrategy: Implementation of EvaluationBudgetStrategy that uses fixed evaluation counts for each problem.
FixedEvaluationsStrategy(List<Integer>) - Constructor for class org.uma.evolver.metaoptimizationproblem.evaluationbudgetstrategy.FixedEvaluationsStrategy: Creates a new FixedEvaluationsStrategy with the specified evaluation counts.
FREQUENCY_OF_APPLICATION_OF_MUTATION_OPERATOR - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
FREQUENCY_SELECTION_MUTATION_BASED_PERTURBATION - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
FUZZY_RECOMBINATION - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADDoubleParameterSpace
FUZZY_RECOMBINATION - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIDoubleParameterSpace
FUZZY_RECOMBINATION_CROSSOVER_ALPHA - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADDoubleParameterSpace
FUZZY_RECOMBINATION_CROSSOVER_ALPHA - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIDoubleParameterSpace

G

generateConfigurationFile(ParameterSpace) - Method in class org.uma.evolver.util.irace.parameterdescriptiongenerator.IraceParameterDescriptionGenerator: Generates and prints the irace configuration for the given parameter space.
get(String) - Method in class org.uma.evolver.parameter.ParameterSpace: Retrieves a parameter by its name.
getAggregationFunction() - Method in class org.uma.evolver.parameter.catalogue.AggregationFunctionParameter: Creates and returns an AggregationFunction instance based on the current parameter value.
getCreateInitialSolutionsStrategy(Problem<BinarySolution>, int) - Method in class org.uma.evolver.parameter.catalogue.createinitialsolutionsparameter.CreateInitialSolutionsBinaryParameter: Creates and returns a SolutionsCreation strategy for binary solutions based on the current parameter value.
getCreateInitialSolutionsStrategy(Problem<DoubleSolution>, int) - Method in class org.uma.evolver.parameter.catalogue.createinitialsolutionsparameter.CreateInitialSolutionsDoubleParameter: Creates and returns a SolutionsCreation strategy for double solutions based on the current parameter value.
getCreateInitialSolutionsStrategy(Problem<PermutationSolution<Integer>>, int) - Method in class org.uma.evolver.parameter.catalogue.createinitialsolutionsparameter.CreateInitialSolutionsPermutationParameter: Creates and returns a SolutionsCreation strategy for permutation solutions based on the current parameter value.
getCreateInitialSolutionsStrategy(Problem<S>, int) - Method in class org.uma.evolver.parameter.catalogue.createinitialsolutionsparameter.CreateInitialSolutionsParameter: Creates and returns a SolutionsCreation strategy based on the current parameter value.
getCrossover() - Method in class org.uma.evolver.parameter.catalogue.crossoverparameter.BinaryCrossoverParameter
getCrossover() - Method in class org.uma.evolver.parameter.catalogue.crossoverparameter.CrossoverParameter: Returns the configured CrossoverOperator instance for the selected crossover type.
getCrossover() - Method in class org.uma.evolver.parameter.catalogue.crossoverparameter.DoubleCrossoverParameter: Returns a configured CrossoverOperator instance for DoubleSolution based on the selected crossover type and its associated parameters.
getCrossover() - Method in class org.uma.evolver.parameter.catalogue.crossoverparameter.PermutationCrossoverParameter
getDensityEstimator() - Method in class org.uma.evolver.parameter.catalogue.DensityEstimatorParameter: Creates and returns a DensityEstimator instance based on the current parameter value.
getEvaluations() - Method in class org.uma.evolver.metaoptimizationproblem.evaluationbudgetstrategy.FixedEvaluationsStrategy: Returns an unmodifiable view of the evaluation counts.
getEvaluations(int) - Method in interface org.uma.evolver.metaoptimizationproblem.evaluationbudgetstrategy.EvaluationBudgetStrategy: Retrieves the number of evaluations to be performed for a specific problem.
getEvaluations(int) - Method in class org.uma.evolver.metaoptimizationproblem.evaluationbudgetstrategy.FixedEvaluationsStrategy
getEvaluations(int) - Method in class org.uma.evolver.metaoptimizationproblem.evaluationbudgetstrategy.RandomRangeEvaluationsStrategy
getExternalArchive() - Method in class org.uma.evolver.parameter.catalogue.ExternalArchiveParameter: Creates and returns an Archive instance based on the current parameter value.
getGlobalBestInitialization() - Method in class org.uma.evolver.parameter.catalogue.GlobalBestInitializationParameter: Creates and returns a GlobalBestInitialization instance based on the current parameter value.
getGlobalBestSelection(Comparator<DoubleSolution>) - Method in class org.uma.evolver.parameter.catalogue.GlobalBestSelectionParameter: Creates and returns a GlobalBestSelection instance based on the current parameter value.
getGlobalBestUpdate() - Method in class org.uma.evolver.parameter.catalogue.GlobalBestUpdateParameter: Creates and returns a GlobalBestUpdate instance based on the current parameter value.
getInertiaWeightComputingStrategy() - Method in class org.uma.evolver.parameter.catalogue.InertiaWeightComputingParameter: Creates and returns an InertiaWeightComputingStrategy instance based on the current parameter value.
getLocalBestInitialization() - Method in class org.uma.evolver.parameter.catalogue.LocalBestInitializationParameter: Creates and returns a LocalBestInitialization instance based on the current parameter value.
getLocalBestUpdate(DominanceComparator<DoubleSolution>) - Method in class org.uma.evolver.parameter.catalogue.LocalBestUpdateParameter: Creates and returns a LocalBestUpdate instance based on the current parameter value.
getMaxEvaluations() - Method in class org.uma.evolver.metaoptimizationproblem.evaluationbudgetstrategy.RandomRangeEvaluationsStrategy: Returns the maximum number of evaluations.
getMinEvaluations() - Method in class org.uma.evolver.metaoptimizationproblem.evaluationbudgetstrategy.RandomRangeEvaluationsStrategy: Returns the minimum number of evaluations.
getMutation() - Method in class org.uma.evolver.parameter.catalogue.mutationparameter.BinaryMutationParameter: Creates and returns a configured mutation operator for binary solutions based on the current parameter value.
getMutation() - Method in class org.uma.evolver.parameter.catalogue.mutationparameter.DoubleMutationParameter: Creates and returns a configured mutation operator for double solutions based on the current parameter value.
getMutation() - Method in class org.uma.evolver.parameter.catalogue.mutationparameter.MutationParameter: Creates and returns a configured MutationOperator instance based on the current parameter value.
getMutation() - Method in class org.uma.evolver.parameter.catalogue.mutationparameter.PermutationMutationParameter: Creates and returns a configured mutation operator for permutation solutions based on the current parameter value.
getNeighborhood() - Method in class org.uma.evolver.algorithm.base.moead.BaseMOEAD: Creates the neighborhood structure for solution interactions.
getParameter() - Method in class org.uma.evolver.parameter.catalogue.DifferentialEvolutionCrossoverParameter: Creates and returns a DifferentialEvolutionCrossover instance based on the current parameter value.
getParameter(int, int, SequenceGenerator<Integer>) - Method in class org.uma.evolver.parameter.catalogue.DifferentialEvolutionSelectionParameter: Creates and returns a Selection operator for Differential Evolution.
getParameterProcessor(String) - Method in class org.uma.evolver.parameter.yaml.YAMLParameterSpace: Returns the parameter processor for the specified parameter type.
getParameterProcessors() - Method in class org.uma.evolver.parameter.yaml.YAMLParameterSpace: Returns an unmodifiable view of all parameter processors.
getPerturbation() - Method in class org.uma.evolver.parameter.catalogue.PerturbationParameter: Creates and returns a Perturbation instance based on the current parameter value.
getPositionUpdate() - Method in class org.uma.evolver.parameter.catalogue.PositionUpdateParameter: Creates and returns a PositionUpdate instance based on the current parameter value.
getRanking() - Method in class org.uma.evolver.parameter.catalogue.RankingParameter: Creates and returns a Ranking instance based on the current parameter value.
getRepairDoubleSolutionStrategy() - Method in class org.uma.evolver.parameter.catalogue.RepairDoubleSolutionStrategyParameter: Creates and returns a RepairDoubleSolution instance based on the current parameter value.
getReplacement() - Method in class org.uma.evolver.parameter.catalogue.ReplacementParameter: Creates and returns a Replacement instance based on the current parameter value.
getSelection(int) - Method in class org.uma.evolver.parameter.catalogue.selectionparameter.DoubleSelectionParameter: Creates and returns a Selection component for double solutions based on the configured selection strategy.
getSelection(int, Comparator<S>) - Method in class org.uma.evolver.parameter.catalogue.selectionparameter.SelectionParameter: Creates and returns a Selection operator based on the current parameter value.
getSequenceGenerator() - Method in class org.uma.evolver.parameter.catalogue.SequenceGeneratorParameter: Creates and returns a SequenceGenerator based on the current parameter value.
getVariation() - Method in class org.uma.evolver.parameter.catalogue.variationparameter.BinaryVariationParameter: Creates and returns a configured variation operator for binary solutions based on the current parameter value.
getVariation() - Method in class org.uma.evolver.parameter.catalogue.variationparameter.DoubleVariationParameter: Creates and returns a configured variation operator for double solutions based on the current parameter value.
getVariation() - Method in class org.uma.evolver.parameter.catalogue.variationparameter.PermutationVariationParameter: Creates and returns a configured variation operator for permutation solutions based on the current parameter value.
getVariation() - Method in class org.uma.evolver.parameter.catalogue.variationparameter.VariationParameter: Creates and returns a configured Variation operator based on the current parameter value.
getVelocityInitialization() - Method in class org.uma.evolver.parameter.catalogue.VelocityInitializationParameter: Creates and returns a VelocityInitialization instance based on the current parameter value.
getVelocityUpdate() - Method in class org.uma.evolver.parameter.catalogue.VelocityUpdateParameter: Creates and returns a VelocityUpdate instance based on the current parameter value.
GLOBAL_BEST_INITIALIZATION - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
GLOBAL_BEST_SELECTION - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
GLOBAL_BEST_UPDATE - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
GlobalBestInitializationParameter - Class in org.uma.evolver.parameter.catalogue: A categorical parameter representing different global best initialization strategies for Particle Swarm Optimization (PSO).
GlobalBestInitializationParameter(String, List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.GlobalBestInitializationParameter: Creates a new GlobalBestInitializationParameter with the specified name and valid values.
GlobalBestInitializationParameter(List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.GlobalBestInitializationParameter: Creates a new GlobalBestInitializationParameter with the specified valid values.
GlobalBestSelectionParameter - Class in org.uma.evolver.parameter.catalogue: A categorical parameter representing different global best selection strategies for Particle Swarm Optimization (PSO).
GlobalBestSelectionParameter(String, List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.GlobalBestSelectionParameter: Creates a new GlobalBestSelectionParameter with the specified name and valid values.
GlobalBestSelectionParameter(List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.GlobalBestSelectionParameter: Creates a new GlobalBestSelectionParameter with the specified valid values.
GlobalBestUpdateParameter - Class in org.uma.evolver.parameter.catalogue: A categorical parameter representing different global best update strategies for Particle Swarm Optimization (PSO).
GlobalBestUpdateParameter(String, List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.GlobalBestUpdateParameter: Constructs a new GlobalBestUpdateParameter instance with the given name and list of update strategies.
GlobalBestUpdateParameter(List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.GlobalBestUpdateParameter: Constructs a new GlobalBestUpdateParameter instance with the given list of update strategies.
globalSubParameters() - Method in class org.uma.evolver.parameter.Parameter: Returns the list of global sub-parameters associated with this parameter.

H

HUX_CROSSOVER - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADBinaryParameterSpace
HUX_CROSSOVER - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIBinaryParameterSpace
HYPERVOLUME_ARCHIVE - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
HypervolumeMinus - Class in org.uma.evolver.util: Class that returns the negative of the hypervolume value.
HypervolumeMinus() - Constructor for class org.uma.evolver.util.HypervolumeMinus

I

INERTIA_WEIGHT - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
INERTIA_WEIGHT_COMPUTING_STRATEGY - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
INERTIA_WEIGHT_MAX - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
INERTIA_WEIGHT_MIN - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
InertiaWeightComputingParameter - Class in org.uma.evolver.parameter.catalogue: A categorical parameter representing different inertia weight computing strategies for Particle Swarm Optimization (PSO).
InertiaWeightComputingParameter(String, List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.InertiaWeightComputingParameter: Creates a new InertiaWeightComputingParameter with the specified name and valid values.
InertiaWeightComputingParameter(List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.InertiaWeightComputingParameter: Creates a new InertiaWeightComputingParameter with the specified valid values.
INSERT - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADPermutationParameterSpace
INSERT - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIPermutationParameterSpace
INSERT - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEAPermutationParameterSpace
INTEGER_SEQUENCE - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADCommonParameterSpace
IntegerParameter - Class in org.uma.evolver.parameter.type: A parameter representing an int value constrained within a specified inclusive range.
IntegerParameter(String, int, int) - Constructor for class org.uma.evolver.parameter.type.IntegerParameter: Constructs an IntegerParameter with the given name and range.
IntegerParameterProcessor - Class in org.uma.evolver.parameter.yaml.processors: Processes integer parameters from YAML configuration.
IntegerParameterProcessor() - Constructor for class org.uma.evolver.parameter.yaml.processors.IntegerParameterProcessor: Creates a new IntegerParameterProcessor.
INVERSION - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADPermutationParameterSpace
INVERSION - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIPermutationParameterSpace
INVERSION - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEAPermutationParameterSpace
IraceMOEADBinaryParameterDescriptionGenerator - Class in org.uma.evolver.util.irace.parameterdescriptiongenerator: Program to generate the irace configuration file for class DoubleNSGAII
IraceMOEADBinaryParameterDescriptionGenerator() - Constructor for class org.uma.evolver.util.irace.parameterdescriptiongenerator.IraceMOEADBinaryParameterDescriptionGenerator
IraceMOEADDoubleParameterDescriptionGenerator - Class in org.uma.evolver.util.irace.parameterdescriptiongenerator: Program to generate the irace configuration file for the MOEA/D algorithm with real-coded solutions.
IraceMOEADDoubleParameterDescriptionGenerator() - Constructor for class org.uma.evolver.util.irace.parameterdescriptiongenerator.IraceMOEADDoubleParameterDescriptionGenerator
IraceMOEADPermutationParameterDescriptionGenerator - Class in org.uma.evolver.util.irace.parameterdescriptiongenerator: Program to generate the irace configuration file for the MOEA/D algorithm with permutation solutions.
IraceMOEADPermutationParameterDescriptionGenerator() - Constructor for class org.uma.evolver.util.irace.parameterdescriptiongenerator.IraceMOEADPermutationParameterDescriptionGenerator
IraceMOPSOParameterDescriptionGenerator - Class in org.uma.evolver.util.irace.parameterdescriptiongenerator: Program to generate the irace configuration file for the MOPSO (Multi-Objective Particle Swarm Optimization) algorithm.
IraceMOPSOParameterDescriptionGenerator() - Constructor for class org.uma.evolver.util.irace.parameterdescriptiongenerator.IraceMOPSOParameterDescriptionGenerator
IraceNSGAIIBinaryParameterDescriptionGenerator - Class in org.uma.evolver.util.irace.parameterdescriptiongenerator: Program to generate the irace configuration file for the NSGA-II algorithm with binary solutions.
IraceNSGAIIBinaryParameterDescriptionGenerator() - Constructor for class org.uma.evolver.util.irace.parameterdescriptiongenerator.IraceNSGAIIBinaryParameterDescriptionGenerator
IraceNSGAIIDoubleParameterDescriptionGenerator - Class in org.uma.evolver.util.irace.parameterdescriptiongenerator: Program to generate the irace configuration file for the NSGA-II algorithm with real-coded solutions.
IraceNSGAIIDoubleParameterDescriptionGenerator() - Constructor for class org.uma.evolver.util.irace.parameterdescriptiongenerator.IraceNSGAIIDoubleParameterDescriptionGenerator
IraceNSGAIIPermutationParameterDescriptionGenerator - Class in org.uma.evolver.util.irace.parameterdescriptiongenerator: Program to generate the irace configuration file for the NSGA-II algorithm with permutation solutions.
IraceNSGAIIPermutationParameterDescriptionGenerator() - Constructor for class org.uma.evolver.util.irace.parameterdescriptiongenerator.IraceNSGAIIPermutationParameterDescriptionGenerator
IraceParameterDescriptionGenerator<S> - Class in org.uma.evolver.util.irace.parameterdescriptiongenerator: A generator for creating parameter description files in the irace configuration format.
IraceParameterDescriptionGenerator() - Constructor for class org.uma.evolver.util.irace.parameterdescriptiongenerator.IraceParameterDescriptionGenerator
IraceRDEMOEADoubleParameterDescriptionGenerator - Class in org.uma.evolver.util.irace.parameterdescriptiongenerator: Program to generate the irace configuration file for the RDS-MOEA/D algorithm with real-coded solutions.
IraceRDEMOEADoubleParameterDescriptionGenerator() - Constructor for class org.uma.evolver.util.irace.parameterdescriptiongenerator.IraceRDEMOEADoubleParameterDescriptionGenerator
IraceRDEMOEAPermutationParameterDescriptionGenerator - Class in org.uma.evolver.util.irace.parameterdescriptiongenerator: Program to generate the irace configuration file for the RDS-MOEA/D algorithm with permutation solutions.
IraceRDEMOEAPermutationParameterDescriptionGenerator() - Constructor for class org.uma.evolver.util.irace.parameterdescriptiongenerator.IraceRDEMOEAPermutationParameterDescriptionGenerator
isTheLowerTheIndicatorValueTheBetter() - Method in class org.uma.evolver.util.EvaluationsQualityIndicator

K

KNN - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEACommonParameterSpace
KNN_NEIGHBORHOOD_SIZE - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEACommonParameterSpace
KNN_NORMALIZE_OBJECTIVES - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEACommonParameterSpace

L

LAPLACE - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADDoubleParameterSpace
LAPLACE - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIDoubleParameterSpace
LAPLACE_CROSSOVER_SCALE - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADDoubleParameterSpace
LAPLACE_CROSSOVER_SCALE - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIDoubleParameterSpace
LATIN_HYPERCUBE_SAMPLING - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADDoubleParameterSpace
LATIN_HYPERCUBE_SAMPLING - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIDoubleParameterSpace
LATIN_HYPERCUBE_SAMPLING - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEADoubleParameterSpace
LATIN_HYPERCUBE_SAMPLING - Static variable in class org.uma.evolver.parameter.catalogue.createinitialsolutionsparameter.CreateInitialSolutionsDoubleParameter: Strategy that uses Latin Hypercube Sampling to ensure good coverage of the search space.
LATIN_HYPERCUBE_SAMPLING_INITIALIZATION - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
LEADER_ARCHIVE - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
leaderArchive - Variable in class org.uma.evolver.algorithm.base.mopso.BaseMOPSO: Archive storing the best solutions found (leaders).
leaderArchiveSize - Variable in class org.uma.evolver.algorithm.base.mopso.BaseMOPSO: The size of the leader archive storing non-dominated solutions.
LEVY_FLIGHT - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADDoubleParameterSpace
LEVY_FLIGHT - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIDoubleParameterSpace
LEVY_FLIGHT_MUTATION_BETA - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADDoubleParameterSpace
LEVY_FLIGHT_MUTATION_BETA - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIDoubleParameterSpace
LEVY_FLIGHT_MUTATION_STEP_SIZE - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADDoubleParameterSpace
LEVY_FLIGHT_MUTATION_STEP_SIZE - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIDoubleParameterSpace
LINEAR_DECREASING_VALUE - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
LINEAR_INCREASING_VALUE - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
LINKED_POLYNOMIAL - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADDoubleParameterSpace
LINKED_POLYNOMIAL - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
LINKED_POLYNOMIAL - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIDoubleParameterSpace
LINKED_POLYNOMIAL - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEADoubleParameterSpace
LINKED_POLYNOMIAL_MUTATION_DISTRIBUTION_INDEX - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADDoubleParameterSpace
LINKED_POLYNOMIAL_MUTATION_DISTRIBUTION_INDEX - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
LINKED_POLYNOMIAL_MUTATION_DISTRIBUTION_INDEX - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIDoubleParameterSpace
LINKED_POLYNOMIAL_MUTATION_DISTRIBUTION_INDEX - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEADoubleParameterSpace
LOCAL_BEST_INITIALIZATION - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
LOCAL_BEST_UPDATE - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
LocalBestInitializationParameter - Class in org.uma.evolver.parameter.catalogue: A categorical parameter representing different local best initialization strategies for Particle Swarm Optimization (PSO).
LocalBestInitializationParameter(String, List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.LocalBestInitializationParameter: Creates a new LocalBestInitializationParameter with the specified name and valid values.
LocalBestInitializationParameter(List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.LocalBestInitializationParameter: Creates a new LocalBestInitializationParameter with the specified valid values.
LocalBestUpdateParameter - Class in org.uma.evolver.parameter.catalogue: A categorical parameter representing different local best update strategies for Particle Swarm Optimization (PSO).
LocalBestUpdateParameter(String, List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.LocalBestUpdateParameter: Constructs a new LocalBestUpdateParameter instance with the given name and list of update strategies.
LocalBestUpdateParameter(List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.LocalBestUpdateParameter: Creates a new LocalBestUpdateParameter with the specified valid values.
lowerBound - Variable in class org.uma.evolver.parameter.type.RangeParameter: Inclusive lower bound of the parameter.

M

main(String[]) - Static method in class org.uma.evolver.example.base.MOEAD_DTLZ2
main(String[]) - Static method in class org.uma.evolver.example.base.MOEADBiObjectiveTSP
main(String[]) - Static method in class org.uma.evolver.example.base.MOEADDE_LZ09F2
main(String[]) - Static method in class org.uma.evolver.example.base.MOEADOneZeroMax
main(String[]) - Static method in class org.uma.evolver.example.base.MOPSO_SMPSO_ZDT4
main(String[]) - Static method in class org.uma.evolver.example.base.MOPSO_ZCAT1
main(String[]) - Static method in class org.uma.evolver.example.base.MOPSOExternalArchiveDTLZ3
main(String[]) - Static method in class org.uma.evolver.example.base.NSGAIIBiObjectiveTSP
main(String[]) - Static method in class org.uma.evolver.example.base.NSGAIIBiObjectiveWithObserversTSP
main(String[]) - Static method in class org.uma.evolver.example.base.NSGAIIDTLZ3Example
main(String[]) - Static method in class org.uma.evolver.example.base.NSGAIIDTLZ3WithArchiveExample
main(String[]) - Static method in class org.uma.evolver.example.base.NSGAIIOneZeroMaxExample
main(String[]) - Static method in class org.uma.evolver.example.base.NSGAIIZDT4Example: Main execution method for the NSGA-II ZDT4 example.
main(String[]) - Static method in class org.uma.evolver.example.base.NSGAIIZDT4ExampleV2
main(String[]) - Static method in class org.uma.evolver.example.base.RDEMOEA_NSGAII_ZDT4Example
main(String[]) - Static method in class org.uma.evolver.example.base.RDEMOEA_SPEA2_DTLZ2Example
main(String[]) - Static method in class org.uma.evolver.example.base.SMSEMOAExample
main(String[]) - Static method in class org.uma.evolver.example.meta.AsyncNSGAIIOptimizingNSGAIIForBenchmarkWFG
main(String[]) - Static method in class org.uma.evolver.example.meta.NSGAIIOptimizingmMOEADForBenchmarkRE3D
main(String[]) - Static method in class org.uma.evolver.example.meta.NSGAIIOptimizingMOEADForBenchmarkDTLZ
main(String[]) - Static method in class org.uma.evolver.example.meta.NSGAIIOptimizingMOEADForProblemZCAT1
main(String[]) - Static method in class org.uma.evolver.example.meta.NSGAIIOptimizingMOEADForProblemZDT4
main(String[]) - Static method in class org.uma.evolver.example.meta.NSGAIIOptimizingMOPSOForBenchmarkDTLZ
main(String[]) - Static method in class org.uma.evolver.example.meta.NSGAIIOptimizingMOPSOForProblemZCAT3
main(String[]) - Static method in class org.uma.evolver.example.meta.NSGAIIOptimizingMOPSOForProblemZDT4
main(String[]) - Static method in class org.uma.evolver.example.meta.NSGAIIOptimizingNSGAIIForBenchmarkDTLZ
main(String[]) - Static method in class org.uma.evolver.example.meta.NSGAIIOptimizingNSGAIIForBenchmarkRE3D
main(String[]) - Static method in class org.uma.evolver.example.meta.NSGAIIOptimizingNSGAIIForBenchmarkWFG
main(String[]) - Static method in class org.uma.evolver.example.meta.NSGAIIOptimizingNSGAIIForBenchmarkZDT
main(String[]) - Static method in class org.uma.evolver.example.meta.NSGAIIOptimizingNSGAIIForBiObjectiveTSP
main(String[]) - Static method in class org.uma.evolver.example.meta.NSGAIIOptimizingNSGAIIForProblemDTLZ3
main(String[]) - Static method in class org.uma.evolver.example.meta.NSGAIIOptimizingNSGAIIForProblemRE31
main(String[]) - Static method in class org.uma.evolver.example.meta.NSGAIIOptimizingNSGAIIForProblemZCAT1
main(String[]) - Static method in class org.uma.evolver.example.meta.NSGAIIOptimizingNSGAIIForProblemZDT4
main(String[]) - Static method in class org.uma.evolver.example.meta.NSGAIIOptimizingNSGAIIForProblemZDT4MinimizingEvaluations
main(String[]) - Static method in class org.uma.evolver.example.meta.NSGAIIOptimizingNSGAIIForTwoBiObjectiveTSP
main(String[]) - Static method in class org.uma.evolver.example.meta.NSGAIIOptimizingRDEMOEAForProblemZDT4
main(String[]) - Static method in class org.uma.evolver.example.meta.NSGAIIOptimizingSMSEMOAForProblemDTLZ3
main(String[]) - Static method in class org.uma.evolver.example.meta.NSGAIIOptimizingSMSEMOAForProblemZDT4
main(String[]) - Static method in class org.uma.evolver.example.meta.SMPSOOptimizingNSGAIIForProblemRE31
main(String[]) - Static method in class org.uma.evolver.util.irace.AutoNSGAIIIraceHV: Main method that runs NSGA-II with the provided configuration and returns the hypervolume value.
main(String[]) - Static method in class org.uma.evolver.util.irace.parameterdescriptiongenerator.IraceMOEADBinaryParameterDescriptionGenerator
main(String[]) - Static method in class org.uma.evolver.util.irace.parameterdescriptiongenerator.IraceMOEADDoubleParameterDescriptionGenerator: Main method that generates and prints the irace configuration for MOEA/D with real-coded solutions.
main(String[]) - Static method in class org.uma.evolver.util.irace.parameterdescriptiongenerator.IraceMOEADPermutationParameterDescriptionGenerator: Main method that generates and prints the irace configuration for MOEA/D with permutation solutions.
main(String[]) - Static method in class org.uma.evolver.util.irace.parameterdescriptiongenerator.IraceMOPSOParameterDescriptionGenerator: Main method that generates and prints the irace configuration for MOPSO.
main(String[]) - Static method in class org.uma.evolver.util.irace.parameterdescriptiongenerator.IraceNSGAIIBinaryParameterDescriptionGenerator: Main method that generates and prints the irace configuration for NSGA-II with binary solutions.
main(String[]) - Static method in class org.uma.evolver.util.irace.parameterdescriptiongenerator.IraceNSGAIIDoubleParameterDescriptionGenerator: Main method that generates and prints the irace configuration for NSGA-II with real-coded solutions.
main(String[]) - Static method in class org.uma.evolver.util.irace.parameterdescriptiongenerator.IraceNSGAIIPermutationParameterDescriptionGenerator: Main method that generates and prints the irace configuration for NSGA-II with permutation solutions.
main(String[]) - Static method in class org.uma.evolver.util.irace.parameterdescriptiongenerator.IraceRDEMOEADoubleParameterDescriptionGenerator: Main method that generates and prints the irace configuration for RDS-MOEA/D with real-coded solutions.
main(String[]) - Static method in class org.uma.evolver.util.irace.parameterdescriptiongenerator.IraceRDEMOEAPermutationParameterDescriptionGenerator: Main method that generates and prints the irace configuration for RDS-MOEA/D with permutation solutions.
MAXIMUM_NUMBER_OF_REPLACED_SOLUTIONS - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADCommonParameterSpace
maximumNumberOfEvaluations - Variable in class org.uma.evolver.algorithm.base.moead.BaseMOEAD: The maximum number of evaluations allowed for the algorithm.
maximumNumberOfEvaluations - Variable in class org.uma.evolver.algorithm.base.mopso.BaseMOPSO: The maximum number of evaluations allowed for the algorithm.
maximumNumberOfEvaluations - Variable in class org.uma.evolver.algorithm.base.nsgaii.BaseNSGAII: The maximum number of evaluations allowed for the algorithm.
maximumNumberOfEvaluations - Variable in class org.uma.evolver.algorithm.base.rdsmoea.BaseRDEMOEA
maximumNumberOfEvaluations - Variable in class org.uma.evolver.algorithm.base.smsemoa.BaseSMSEMOA
maximumNumberOfReplacedSolutions - Variable in class org.uma.evolver.algorithm.base.moead.BaseMOEAD: Maximum number of solutions to replace in the neighborhood.
maxValue() - Method in class org.uma.evolver.parameter.type.RangeParameter: Returns the maximum valid value (upper bound) for this parameter.
MetaAsyncNSGAIIBuilder - Class in org.uma.evolver.algorithm.meta: Builder for creating asynchronous multi-threaded NSGA-II instances for optimization tasks.
MetaAsyncNSGAIIBuilder(Problem<DoubleSolution>) - Constructor for class org.uma.evolver.algorithm.meta.MetaAsyncNSGAIIBuilder: Creates a new builder with the specified problem.
MetaNSGAIIBuilder - Class in org.uma.evolver.algorithm.meta: Builder for creating NSGA-II instances configured for meta-optimization tasks with double solutions.
MetaNSGAIIBuilder(MetaOptimizationProblem<?>, ParameterSpace) - Constructor for class org.uma.evolver.algorithm.meta.MetaNSGAIIBuilder: Creates a new builder with the specified meta-optimization problem.
MetaOptimizationProblem<S> - Class in org.uma.evolver.metaoptimizationproblem: A meta-optimization problem that optimizes the parameters of an optimization algorithm by evaluating its performance across multiple problem instances using quality indicators.
MetaOptimizationProblem(BaseLevelAlgorithm<S>, List<Problem<S>>, List<String>, List<QualityIndicator>, EvaluationBudgetStrategy, int) - Constructor for class org.uma.evolver.metaoptimizationproblem.MetaOptimizationProblem: Constructs a new meta-optimization problem instance.
MetaSMPSOBuilder - Class in org.uma.evolver.algorithm.meta: Builder for creating SMPSO (Speed-constrained Multi-objective Particle Swarm Optimization) instances configured for meta-optimization tasks.
MetaSMPSOBuilder(MetaOptimizationProblem<?>) - Constructor for class org.uma.evolver.algorithm.meta.MetaSMPSOBuilder: Creates a new builder with the specified meta-optimization problem.
minValue() - Method in class org.uma.evolver.parameter.type.RangeParameter: Returns the minimum valid value (lower bound) for this parameter.
MODIFIED_TSCHEBYSCHEFF - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADCommonParameterSpace
MOEAD_DTLZ2 - Class in org.uma.evolver.example.base
MOEAD_DTLZ2() - Constructor for class org.uma.evolver.example.base.MOEAD_DTLZ2
MOEADBinaryParameterSpace - Class in org.uma.evolver.algorithm.base.moead.parameterspace: Parameter space for the MOEA/D algorithm using binary solutions.
MOEADBinaryParameterSpace() - Constructor for class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADBinaryParameterSpace
MOEADBiObjectiveTSP - Class in org.uma.evolver.example.base: Class configuring MOEA/D using arguments in the form <key, value>
MOEADBiObjectiveTSP() - Constructor for class org.uma.evolver.example.base.MOEADBiObjectiveTSP
MOEADCommonParameterSpace<S> - Class in org.uma.evolver.algorithm.base.moead.parameterspace: Base parameter space for the MOEA/D algorithm.
MOEADCommonParameterSpace() - Constructor for class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADCommonParameterSpace
MOEADDE_LZ09F2 - Class in org.uma.evolver.example.base
MOEADDE_LZ09F2() - Constructor for class org.uma.evolver.example.base.MOEADDE_LZ09F2
MOEADDoubleParameterSpace - Class in org.uma.evolver.algorithm.base.moead.parameterspace: Parameter space for the MOEA/D algorithm using real-coded (double) solutions.
MOEADDoubleParameterSpace() - Constructor for class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADDoubleParameterSpace
MOEADOneZeroMax - Class in org.uma.evolver.example.base: Class configuring MOEA/D using arguments in the form <key, value>
MOEADOneZeroMax() - Constructor for class org.uma.evolver.example.base.MOEADOneZeroMax
MOEADPermutationParameterSpace - Class in org.uma.evolver.algorithm.base.moead.parameterspace: Parameter space for the MOEA/D algorithm using permutation-based solutions.
MOEADPermutationParameterSpace() - Constructor for class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADPermutationParameterSpace
MOPSO_SMPSO_ZDT4 - Class in org.uma.evolver.example.base
MOPSO_SMPSO_ZDT4() - Constructor for class org.uma.evolver.example.base.MOPSO_SMPSO_ZDT4
MOPSO_ZCAT1 - Class in org.uma.evolver.example.base
MOPSO_ZCAT1() - Constructor for class org.uma.evolver.example.base.MOPSO_ZCAT1
MOPSOExternalArchiveDTLZ3 - Class in org.uma.evolver.example.base
MOPSOExternalArchiveDTLZ3() - Constructor for class org.uma.evolver.example.base.MOPSOExternalArchiveDTLZ3
MOPSOParameterFactory - Class in org.uma.evolver.parameter.factory: Factory class for creating and configuring categorical parameters specific to the MOPSO algorithm.
MOPSOParameterFactory() - Constructor for class org.uma.evolver.parameter.factory.MOPSOParameterFactory
MOPSOParameterSpace - Class in org.uma.evolver.algorithm.base.mopso: Parameter space configuration for Multi-Objective Particle Swarm Optimization (MOPSO) algorithms.
MOPSOParameterSpace() - Constructor for class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
MUTATION - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADBinaryParameterSpace
MUTATION - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADDoubleParameterSpace
MUTATION - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADPermutationParameterSpace
MUTATION - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
MUTATION - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIICommonParameterSpace
MUTATION - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEACommonParameterSpace
MUTATION_PROBABILITY - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADPermutationParameterSpace
MUTATION_PROBABILITY - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIPermutationParameterSpace
MUTATION_PROBABILITY - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEAPermutationParameterSpace
MUTATION_PROBABILITY_FACTOR - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADBinaryParameterSpace
MUTATION_PROBABILITY_FACTOR - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADDoubleParameterSpace
MUTATION_PROBABILITY_FACTOR - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
MUTATION_PROBABILITY_FACTOR - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIBinaryParameterSpace
MUTATION_PROBABILITY_FACTOR - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIDoubleParameterSpace
MUTATION_PROBABILITY_FACTOR - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEADoubleParameterSpace
MUTATION_REPAIR_STRATEGY - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADDoubleParameterSpace
MUTATION_REPAIR_STRATEGY - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
MUTATION_REPAIR_STRATEGY - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIDoubleParameterSpace
MUTATION_REPAIR_STRATEGY - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEADoubleParameterSpace
MutationParameter<S> - Class in org.uma.evolver.parameter.catalogue.mutationparameter: Abstract parameter class representing a configurable mutation operator for evolutionary algorithms.
MutationParameter(String, List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.mutationparameter.MutationParameter
MutationParameter(List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.mutationparameter.MutationParameter: Constructs a mutation parameter with the given list of available mutation operator names.

N

name() - Method in class org.uma.evolver.metaoptimizationproblem.MetaOptimizationProblem: Returns the name of the problem.
name() - Method in class org.uma.evolver.parameter.catalogue.AggregationFunctionParameter: Returns the name of this parameter.
name() - Method in class org.uma.evolver.parameter.catalogue.DensityEstimatorParameter: Returns the name of this parameter.
name() - Method in class org.uma.evolver.parameter.catalogue.DifferentialEvolutionCrossoverParameter: Returns the name of this parameter.
name() - Method in class org.uma.evolver.parameter.catalogue.DifferentialEvolutionSelectionParameter: Returns the name of this parameter.
name() - Method in class org.uma.evolver.parameter.catalogue.ExternalArchiveParameter: Returns the name of this parameter.
name() - Method in class org.uma.evolver.parameter.catalogue.GlobalBestInitializationParameter: Returns the name of this parameter.
name() - Method in class org.uma.evolver.parameter.catalogue.GlobalBestSelectionParameter: Returns the name of this parameter.
name() - Method in class org.uma.evolver.parameter.catalogue.GlobalBestUpdateParameter: Returns the name of this parameter.
name() - Method in class org.uma.evolver.parameter.catalogue.InertiaWeightComputingParameter: Returns the name of this parameter.
name() - Method in class org.uma.evolver.parameter.catalogue.LocalBestInitializationParameter: Returns the name of this parameter.
name() - Method in class org.uma.evolver.parameter.catalogue.LocalBestUpdateParameter: Returns the name of this parameter.
name() - Method in class org.uma.evolver.parameter.catalogue.PerturbationParameter: Returns the name of this parameter.
name() - Method in class org.uma.evolver.parameter.catalogue.PositionUpdateParameter: Returns the name of this parameter.
name() - Method in class org.uma.evolver.parameter.catalogue.RankingParameter: Returns the name of this parameter.
name() - Method in class org.uma.evolver.parameter.catalogue.RepairDoubleSolutionStrategyParameter: Returns the name of this parameter.
name() - Method in class org.uma.evolver.parameter.catalogue.ReplacementParameter: Returns the name of this parameter.
name() - Method in class org.uma.evolver.parameter.catalogue.selectionparameter.SelectionParameter: Returns the name of this parameter.
name() - Method in class org.uma.evolver.parameter.catalogue.SequenceGeneratorParameter: Returns the name of this parameter.
name() - Method in class org.uma.evolver.parameter.catalogue.VelocityInitializationParameter: Returns the name of this parameter.
name() - Method in class org.uma.evolver.parameter.catalogue.VelocityUpdateParameter: Returns the name of this parameter.
name() - Method in class org.uma.evolver.parameter.Parameter: Returns the name of this parameter.
name() - Method in class org.uma.evolver.util.EvaluationsQualityIndicator
name() - Method in class org.uma.evolver.util.HypervolumeMinus
name() - Method in class org.uma.evolver.util.problemfamilyinfo.DTLZ3DProblemFamilyInfo
name() - Method in interface org.uma.evolver.util.problemfamilyinfo.ProblemFamilyInfo
name() - Method in class org.uma.evolver.util.problemfamilyinfo.RE3DProblemFamilyInfo
name() - Method in class org.uma.evolver.util.problemfamilyinfo.WFG2DProblemFamilyInfo
name() - Method in class org.uma.evolver.util.problemfamilyinfo.ZDTProblemFamilyInfo
neighborhood - Variable in class org.uma.evolver.algorithm.base.moead.BaseMOEAD: Neighborhood structure for solution interactions.
NEIGHBORHOOD_SELECTION_PROBABILITY - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADCommonParameterSpace
NEIGHBORHOOD_SIZE - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADCommonParameterSpace
newInstance() - Method in class org.uma.evolver.util.EvaluationsQualityIndicator
newInstance() - Method in class org.uma.evolver.util.HypervolumeMinus
NON_UNIFORM - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADDoubleParameterSpace
NON_UNIFORM - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
NON_UNIFORM - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIDoubleParameterSpace
NON_UNIFORM - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEADoubleParameterSpace
NON_UNIFORM_MUTATION_PERTURBATION - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADDoubleParameterSpace
NON_UNIFORM_MUTATION_PERTURBATION - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
NON_UNIFORM_MUTATION_PERTURBATION - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIDoubleParameterSpace
NON_UNIFORM_MUTATION_PERTURBATION - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEADoubleParameterSpace
nonConfigurableSubParameters() - Method in class org.uma.evolver.parameter.Parameter: Returns a map of non-configurable sub-parameters associated with this parameter.
NORMALIZE_OBJECTIVES - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADCommonParameterSpace
normalizedObjectives - Variable in class org.uma.evolver.algorithm.base.moead.BaseMOEAD: Flag indicating whether objectives should be normalized.
normalizedObjectives(boolean) - Method in class org.uma.evolver.parameter.catalogue.AggregationFunctionParameter: Sets whether the objectives should be normalized before aggregation.
NSGAIIBinaryParameterSpace - Class in org.uma.evolver.algorithm.base.nsgaii.parameterspace: Parameter space for NSGA-II algorithm variants using binary-coded solutions.
NSGAIIBinaryParameterSpace() - Constructor for class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIBinaryParameterSpace
NSGAIIBiObjectiveTSP - Class in org.uma.evolver.example.base: This class demonstrates the configuration and execution of the NSGA-II (Non-dominated Sorting Genetic Algorithm II) for solving bi-objective Traveling Salesman Problem (TSP) instances.
NSGAIIBiObjectiveTSP() - Constructor for class org.uma.evolver.example.base.NSGAIIBiObjectiveTSP
NSGAIIBiObjectiveWithObserversTSP - Class in org.uma.evolver.example.base: This class demonstrates the configuration and execution of NSGA-II (Non-dominated Sorting Genetic Algorithm II) for solving bi-objective Traveling Salesman Problem (TSP) instances, with additional runtime visualization.
NSGAIIBiObjectiveWithObserversTSP() - Constructor for class org.uma.evolver.example.base.NSGAIIBiObjectiveWithObserversTSP
NSGAIICommonParameterSpace<S> - Class in org.uma.evolver.algorithm.base.nsgaii.parameterspace: Abstract parameter space for NSGA-II algorithm variants.
NSGAIICommonParameterSpace() - Constructor for class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIICommonParameterSpace
NSGAIIDoubleParameterSpace - Class in org.uma.evolver.algorithm.base.nsgaii.parameterspace: Parameter space for NSGA-II algorithm variants using real-coded (double) solutions.
NSGAIIDoubleParameterSpace() - Constructor for class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIDoubleParameterSpace
NSGAIIDTLZ3Example - Class in org.uma.evolver.example.base
NSGAIIDTLZ3Example() - Constructor for class org.uma.evolver.example.base.NSGAIIDTLZ3Example
NSGAIIDTLZ3WithArchiveExample - Class in org.uma.evolver.example.base
NSGAIIDTLZ3WithArchiveExample() - Constructor for class org.uma.evolver.example.base.NSGAIIDTLZ3WithArchiveExample
NSGAIIOneZeroMaxExample - Class in org.uma.evolver.example.base
NSGAIIOneZeroMaxExample() - Constructor for class org.uma.evolver.example.base.NSGAIIOneZeroMaxExample
NSGAIIOptimizingmMOEADForBenchmarkRE3D - Class in org.uma.evolver.example.meta: Class for running NSGA-II as meta-optimizer to configure DoubleNSGAII using the RE problems with three objectives as the training set.
NSGAIIOptimizingmMOEADForBenchmarkRE3D() - Constructor for class org.uma.evolver.example.meta.NSGAIIOptimizingmMOEADForBenchmarkRE3D
NSGAIIOptimizingMOEADForBenchmarkDTLZ - Class in org.uma.evolver.example.meta: Class for running NSGA-II as meta-optimizer to configure DoubleMOEAD using problem the DTLZ problem family as training set.
NSGAIIOptimizingMOEADForBenchmarkDTLZ() - Constructor for class org.uma.evolver.example.meta.NSGAIIOptimizingMOEADForBenchmarkDTLZ
NSGAIIOptimizingMOEADForProblemZCAT1 - Class in org.uma.evolver.example.meta: Class for running NSGA-II as meta-optimizer to configure DoubleMOEAD using problem ZDT4 as training set.
NSGAIIOptimizingMOEADForProblemZCAT1() - Constructor for class org.uma.evolver.example.meta.NSGAIIOptimizingMOEADForProblemZCAT1
NSGAIIOptimizingMOEADForProblemZDT4 - Class in org.uma.evolver.example.meta: Class for running NSGA-II as meta-optimizer to configure DoubleMOEAD using problem ZDT4 as training set.
NSGAIIOptimizingMOEADForProblemZDT4() - Constructor for class org.uma.evolver.example.meta.NSGAIIOptimizingMOEADForProblemZDT4
NSGAIIOptimizingMOPSOForBenchmarkDTLZ - Class in org.uma.evolver.example.meta: Class for running NSGA-II as meta-optimizer to configure BaseMOPSO using problem DTLZ problems as training set.
NSGAIIOptimizingMOPSOForBenchmarkDTLZ() - Constructor for class org.uma.evolver.example.meta.NSGAIIOptimizingMOPSOForBenchmarkDTLZ
NSGAIIOptimizingMOPSOForProblemZCAT3 - Class in org.uma.evolver.example.meta: Class for running NSGA-II as meta-optimizer to configure BaseMOPSO using problem ZDT4 as training set.
NSGAIIOptimizingMOPSOForProblemZCAT3() - Constructor for class org.uma.evolver.example.meta.NSGAIIOptimizingMOPSOForProblemZCAT3
NSGAIIOptimizingMOPSOForProblemZDT4 - Class in org.uma.evolver.example.meta: Class for running NSGA-II as meta-optimizer to configure BaseMOPSO using problem ZDT4 as training set.
NSGAIIOptimizingMOPSOForProblemZDT4() - Constructor for class org.uma.evolver.example.meta.NSGAIIOptimizingMOPSOForProblemZDT4
NSGAIIOptimizingNSGAIIForBenchmarkDTLZ - Class in org.uma.evolver.example.meta: Class for running NSGA-II as meta-optimizer to configure DoubleNSGAII using problem ZDT4 as the training set.
NSGAIIOptimizingNSGAIIForBenchmarkDTLZ() - Constructor for class org.uma.evolver.example.meta.NSGAIIOptimizingNSGAIIForBenchmarkDTLZ
NSGAIIOptimizingNSGAIIForBenchmarkRE3D - Class in org.uma.evolver.example.meta: Class for running NSGA-II as meta-optimizer to configure DoubleNSGAII using the RE problems with three objectives as the training set.
NSGAIIOptimizingNSGAIIForBenchmarkRE3D() - Constructor for class org.uma.evolver.example.meta.NSGAIIOptimizingNSGAIIForBenchmarkRE3D
NSGAIIOptimizingNSGAIIForBenchmarkWFG - Class in org.uma.evolver.example.meta: Class for running NSGA-II as meta-optimizer to configure DoubleNSGAII using problem ZDT4 as training set.
NSGAIIOptimizingNSGAIIForBenchmarkWFG() - Constructor for class org.uma.evolver.example.meta.NSGAIIOptimizingNSGAIIForBenchmarkWFG
NSGAIIOptimizingNSGAIIForBenchmarkZDT - Class in org.uma.evolver.example.meta: Class for running NSGA-II as meta-optimizer to configure DoubleNSGAII using the ZDT problems as the training set.
NSGAIIOptimizingNSGAIIForBenchmarkZDT() - Constructor for class org.uma.evolver.example.meta.NSGAIIOptimizingNSGAIIForBenchmarkZDT
NSGAIIOptimizingNSGAIIForBiObjectiveTSP - Class in org.uma.evolver.example.meta: Class for running NSGA-II as meta-optimizer to configure PermutationNSGAII using problem KroAB100TSP as training set.
NSGAIIOptimizingNSGAIIForBiObjectiveTSP() - Constructor for class org.uma.evolver.example.meta.NSGAIIOptimizingNSGAIIForBiObjectiveTSP
NSGAIIOptimizingNSGAIIForProblemDTLZ3 - Class in org.uma.evolver.example.meta: Class for running NSGA-II as meta-optimizer to configure DoubleNSGAII using problem DTLZ3 as training set.
NSGAIIOptimizingNSGAIIForProblemDTLZ3() - Constructor for class org.uma.evolver.example.meta.NSGAIIOptimizingNSGAIIForProblemDTLZ3
NSGAIIOptimizingNSGAIIForProblemRE31 - Class in org.uma.evolver.example.meta: Class for running NSGA-II as meta-optimizer to configure DoubleNSGAII using problem RE31 as training set.
NSGAIIOptimizingNSGAIIForProblemRE31() - Constructor for class org.uma.evolver.example.meta.NSGAIIOptimizingNSGAIIForProblemRE31
NSGAIIOptimizingNSGAIIForProblemZCAT1 - Class in org.uma.evolver.example.meta: Class for running NSGA-II as meta-optimizer to configure DoubleNSGAII using problem ZDT4 as training set.
NSGAIIOptimizingNSGAIIForProblemZCAT1() - Constructor for class org.uma.evolver.example.meta.NSGAIIOptimizingNSGAIIForProblemZCAT1
NSGAIIOptimizingNSGAIIForProblemZDT4 - Class in org.uma.evolver.example.meta: Class for running NSGA-II as meta-optimizer to configure DoubleNSGAII using problem ZDT4 as the training set.
NSGAIIOptimizingNSGAIIForProblemZDT4() - Constructor for class org.uma.evolver.example.meta.NSGAIIOptimizingNSGAIIForProblemZDT4
NSGAIIOptimizingNSGAIIForProblemZDT4MinimizingEvaluations - Class in org.uma.evolver.example.meta: Class for running NSGA-II as meta-optimizer to configure DoubleNSGAII using problem ZDT4 as training set.
NSGAIIOptimizingNSGAIIForProblemZDT4MinimizingEvaluations() - Constructor for class org.uma.evolver.example.meta.NSGAIIOptimizingNSGAIIForProblemZDT4MinimizingEvaluations
NSGAIIOptimizingNSGAIIForTwoBiObjectiveTSP - Class in org.uma.evolver.example.meta: Class for running NSGA-II as meta-optimizer to configure PermutationNSGAII using problem KroAB100TSP as training set.
NSGAIIOptimizingNSGAIIForTwoBiObjectiveTSP() - Constructor for class org.uma.evolver.example.meta.NSGAIIOptimizingNSGAIIForTwoBiObjectiveTSP
NSGAIIOptimizingRDEMOEAForProblemZDT4 - Class in org.uma.evolver.example.meta: Class for running NSGA-II as meta-optimizer to configure DoubleNSGAII using problem ZDT4 as training set.
NSGAIIOptimizingRDEMOEAForProblemZDT4() - Constructor for class org.uma.evolver.example.meta.NSGAIIOptimizingRDEMOEAForProblemZDT4
NSGAIIOptimizingSMSEMOAForProblemDTLZ3 - Class in org.uma.evolver.example.meta: Class for running NSGA-II as meta-optimizer to configure DoubleSMSEMOA using problem ZDT4 as training set.
NSGAIIOptimizingSMSEMOAForProblemDTLZ3() - Constructor for class org.uma.evolver.example.meta.NSGAIIOptimizingSMSEMOAForProblemDTLZ3
NSGAIIOptimizingSMSEMOAForProblemZDT4 - Class in org.uma.evolver.example.meta: Class for running NSGA-II as meta-optimizer to configure DoubleSMSEMOA using problem ZDT4 as training set.
NSGAIIOptimizingSMSEMOAForProblemZDT4() - Constructor for class org.uma.evolver.example.meta.NSGAIIOptimizingSMSEMOAForProblemZDT4
NSGAIIPermutationParameterSpace - Class in org.uma.evolver.algorithm.base.nsgaii.parameterspace: Parameter space for NSGA-II algorithm variants using permutation-based solutions.
NSGAIIPermutationParameterSpace() - Constructor for class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIPermutationParameterSpace
NSGAIIZDT4Example - Class in org.uma.evolver.example.base: Example: Running NSGA-II on ZDT4 Problem This example demonstrates how to configure and execute the NSGA-II algorithm to solve the ZDT4 multi-objective optimization problem using the Evolver framework.
NSGAIIZDT4Example() - Constructor for class org.uma.evolver.example.base.NSGAIIZDT4Example
NSGAIIZDT4ExampleV2 - Class in org.uma.evolver.example.base
NSGAIIZDT4ExampleV2() - Constructor for class org.uma.evolver.example.base.NSGAIIZDT4ExampleV2
numberOfConstraints() - Method in class org.uma.evolver.metaoptimizationproblem.MetaOptimizationProblem: Returns the number of constraints in the problem.
numberOfObjectives() - Method in class org.uma.evolver.metaoptimizationproblem.MetaOptimizationProblem: Returns the number of objectives in the problem.
numberOfVariables() - Method in class org.uma.evolver.metaoptimizationproblem.MetaOptimizationProblem: Returns the number of variables (parameters) in the problem.

O

OFFSPRING_POPULATION_SIZE - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIICommonParameterSpace
OFFSPRING_POPULATION_SIZE - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEACommonParameterSpace
offspringPopulationSize - Variable in class org.uma.evolver.algorithm.base.nsgaii.BaseNSGAII: The size of the offspring population generated in each generation.
ONE_SHOT - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEACommonParameterSpace
org.uma.evolver.algorithm.base - package org.uma.evolver.algorithm.base
org.uma.evolver.algorithm.base.moead - package org.uma.evolver.algorithm.base.moead
org.uma.evolver.algorithm.base.moead.parameterspace - package org.uma.evolver.algorithm.base.moead.parameterspace
org.uma.evolver.algorithm.base.mopso - package org.uma.evolver.algorithm.base.mopso
org.uma.evolver.algorithm.base.nsgaii - package org.uma.evolver.algorithm.base.nsgaii
org.uma.evolver.algorithm.base.nsgaii.parameterspace - package org.uma.evolver.algorithm.base.nsgaii.parameterspace
org.uma.evolver.algorithm.base.rdsmoea - package org.uma.evolver.algorithm.base.rdsmoea
org.uma.evolver.algorithm.base.rdsmoea.parameterspace - package org.uma.evolver.algorithm.base.rdsmoea.parameterspace
org.uma.evolver.algorithm.base.smsemoa - package org.uma.evolver.algorithm.base.smsemoa
org.uma.evolver.algorithm.meta - package org.uma.evolver.algorithm.meta
org.uma.evolver.example.base - package org.uma.evolver.example.base
org.uma.evolver.example.meta - package org.uma.evolver.example.meta
org.uma.evolver.metaoptimizationproblem - package org.uma.evolver.metaoptimizationproblem
org.uma.evolver.metaoptimizationproblem.evaluationbudgetstrategy - package org.uma.evolver.metaoptimizationproblem.evaluationbudgetstrategy
org.uma.evolver.parameter - package org.uma.evolver.parameter
org.uma.evolver.parameter.catalogue - package org.uma.evolver.parameter.catalogue
org.uma.evolver.parameter.catalogue.createinitialsolutionsparameter - package org.uma.evolver.parameter.catalogue.createinitialsolutionsparameter
org.uma.evolver.parameter.catalogue.crossoverparameter - package org.uma.evolver.parameter.catalogue.crossoverparameter
org.uma.evolver.parameter.catalogue.mutationparameter - package org.uma.evolver.parameter.catalogue.mutationparameter
org.uma.evolver.parameter.catalogue.selectionparameter - package org.uma.evolver.parameter.catalogue.selectionparameter
org.uma.evolver.parameter.catalogue.variationparameter - package org.uma.evolver.parameter.catalogue.variationparameter
org.uma.evolver.parameter.factory - package org.uma.evolver.parameter.factory
org.uma.evolver.parameter.type - package org.uma.evolver.parameter.type
org.uma.evolver.parameter.yaml - package org.uma.evolver.parameter.yaml
org.uma.evolver.parameter.yaml.processors - package org.uma.evolver.parameter.yaml.processors
org.uma.evolver.util - package org.uma.evolver.util
org.uma.evolver.util.irace - package org.uma.evolver.util.irace
org.uma.evolver.util.irace.parameterdescriptiongenerator - package org.uma.evolver.util.irace.parameterdescriptiongenerator
org.uma.evolver.util.problemfamilyinfo - package org.uma.evolver.util.problemfamilyinfo
OutputResults - Class in org.uma.evolver.util
OutputResults(String, MetaOptimizationProblem<?>, String, List<QualityIndicator>, String) - Constructor for class org.uma.evolver.util.OutputResults
OXD - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADPermutationParameterSpace
OXD - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIPermutationParameterSpace
OXD - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEAPermutationParameterSpace

P

parameter() - Method in class org.uma.evolver.parameter.ConditionalParameter: Returns the parameter that becomes active when the condition is satisfied.
Parameter<T> - Class in org.uma.evolver.parameter: Represents a configurable parameter with a value of type T, supporting hierarchical sub-parameters.
Parameter(String) - Constructor for class org.uma.evolver.parameter.Parameter: Constructs a parameter with the given name.
ParameterFactory<S> - Interface in org.uma.evolver.parameter.factory: A factory interface for creating CategoricalParameter instances specific to different types of solutions.
parameterFlattening(List<Parameter<?>>) - Static method in class org.uma.evolver.parameter.ParameterManagement: Given a list of parameters, returns a list with all of them and all of their sub-parameters
ParameterManagement - Class in org.uma.evolver.parameter
ParameterManagement() - Constructor for class org.uma.evolver.parameter.ParameterManagement
ParameterProcessor - Interface in org.uma.evolver.parameter.yaml: Interface for parameter processors that handle different types of parameters.
parameters() - Method in class org.uma.evolver.metaoptimizationproblem.MetaOptimizationProblem: Returns the list of parameters being optimized.
parameters() - Method in class org.uma.evolver.parameter.ParameterSpace: Returns an unmodifiable view of all parameters in this parameter space.
parameterSpace - Variable in class org.uma.evolver.algorithm.base.moead.BaseMOEAD: The parameter space containing all configurable components and parameters.
parameterSpace - Variable in class org.uma.evolver.algorithm.base.nsgaii.BaseNSGAII: The parameter space containing all configurable components and parameters.
parameterSpace - Variable in class org.uma.evolver.algorithm.base.rdsmoea.BaseRDEMOEA
parameterSpace - Variable in class org.uma.evolver.algorithm.base.smsemoa.BaseSMSEMOA
parameterSpace - Variable in class org.uma.evolver.parameter.ParameterSpace
parameterSpace() - Method in interface org.uma.evolver.algorithm.base.BaseLevelAlgorithm: Returns the parameter space associated with this algorithm.
parameterSpace() - Method in class org.uma.evolver.algorithm.base.moead.BaseMOEAD: Returns the parameter space used by this algorithm.
parameterSpace() - Method in class org.uma.evolver.algorithm.base.mopso.BaseMOPSO: Returns the parameter space used by this algorithm.
parameterSpace() - Method in class org.uma.evolver.algorithm.base.nsgaii.BaseNSGAII: Returns the parameter space used by this algorithm.
parameterSpace() - Method in class org.uma.evolver.algorithm.base.rdsmoea.BaseRDEMOEA: Returns the parameter space associated with this algorithm.
parameterSpace() - Method in class org.uma.evolver.algorithm.base.smsemoa.BaseSMSEMOA: Returns the parameter space associated with this algorithm.
ParameterSpace - Class in org.uma.evolver.parameter: Abstract class that defines a configurable parameter space for metaheuristics.
ParameterSpace() - Constructor for class org.uma.evolver.parameter.ParameterSpace: Constructs a new, empty ParameterSpace.
parse(String[]) - Method in interface org.uma.evolver.algorithm.base.BaseLevelAlgorithm: Parses the given arguments and configures all top-level parameters in the parameter space.
parse(String[]) - Method in class org.uma.evolver.parameter.Parameter: Parses the value for this parameter from the given arguments.
parse(String[]) - Method in class org.uma.evolver.parameter.type.BooleanParameter: Parses the parameter value from a list of command-line-style arguments.
parse(String[]) - Method in class org.uma.evolver.parameter.type.CategoricalIntegerParameter: Parses the parameter value from a list of arguments and validates it.
parse(String[]) - Method in class org.uma.evolver.parameter.type.CategoricalParameter: Parses the parameter value from a list of arguments and validates it.
parse(String[]) - Method in class org.uma.evolver.parameter.type.RangeParameter: Parses the parameter value from a string array and validates it against the defined range.
parse(String[]) - Method in class org.uma.evolver.parameter.type.StringParameter
parse(Function<String, T>, String[]) - Method in class org.uma.evolver.parameter.Parameter: Parses the value for this parameter using the provided function and arguments, and also parses all global and specific sub-parameters.
parseConditionalParameters(T, String[]) - Method in class org.uma.evolver.parameter.ConditionalParameterManager: Parses arguments for all conditional parameters whose conditions are satisfied by the given main parameter value.
parseValue(String) - Method in class org.uma.evolver.parameter.type.DoubleParameter: Parses a string into a Double.
parseValue(String) - Method in class org.uma.evolver.parameter.type.IntegerParameter: Parses a string into an Integer.
parseValue(String) - Method in class org.uma.evolver.parameter.type.RangeParameter: Converts a string into a value of type T.
ParticleSwarmOptimizationBuilder - Class in org.uma.evolver.algorithm.base: A builder class for creating instances of ParticleSwarmOptimizationAlgorithm with optional archive support.
ParticleSwarmOptimizationBuilder() - Constructor for class org.uma.evolver.algorithm.base.ParticleSwarmOptimizationBuilder
PBI_THETA - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADCommonParameterSpace
PCX - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIDoubleParameterSpace
PCX_CROSSOVER_ETA - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIDoubleParameterSpace
PCX_CROSSOVER_ZETA - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIDoubleParameterSpace
PENALTY_BOUNDARY_INTERSECTION - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADCommonParameterSpace
PERMUTATION - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADCommonParameterSpace
PermutationCrossoverParameter - Class in org.uma.evolver.parameter.catalogue.crossoverparameter: Parameter class representing the configuration and factory for crossover operators for PermutationSolution in evolutionary algorithms.
PermutationCrossoverParameter(String, List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.crossoverparameter.PermutationCrossoverParameter
PermutationCrossoverParameter(List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.crossoverparameter.PermutationCrossoverParameter
PermutationMOEAD - Class in org.uma.evolver.algorithm.base.moead: Configurable implementation of the MOEA/D algorithm for permutation-based problems.
PermutationMOEAD(int, String, MOEADPermutationParameterSpace) - Constructor for class org.uma.evolver.algorithm.base.moead.PermutationMOEAD: Constructs a new PermutationMOEAD instance with the specified population size, weight vector files directory, and parameter space.
PermutationMOEAD(Problem<PermutationSolution<Integer>>, int, int, String, ParameterSpace) - Constructor for class org.uma.evolver.algorithm.base.moead.PermutationMOEAD: Constructs a fully configured PermutationMOEAD instance ready for execution.
PermutationMutationParameter - Class in org.uma.evolver.parameter.catalogue.mutationparameter: A parameter class for configuring mutation operators specifically designed for permutation solutions.
PermutationMutationParameter(String, List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.mutationparameter.PermutationMutationParameter: Constructs a new MutationPermutationParameter with the specified list of mutation operator names.
PermutationMutationParameter(List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.mutationparameter.PermutationMutationParameter: Constructs a new MutationPermutationParameter with the specified list of mutation operator names.
PermutationNSGAII - Class in org.uma.evolver.algorithm.base.nsgaii: A configurable implementation of the Non-dominated Sorting Genetic Algorithm II (NSGA-II) specifically designed for permutation-based optimization problems.
PermutationNSGAII(int, ParameterSpace) - Constructor for class org.uma.evolver.algorithm.base.nsgaii.PermutationNSGAII: Constructs a new instance of PermutationNSGAII with the specified population size and parameter space.
PermutationNSGAII(Problem<PermutationSolution<Integer>>, int, int, ParameterSpace) - Constructor for class org.uma.evolver.algorithm.base.nsgaii.PermutationNSGAII: Constructs a fully configured PermutationNSGAII instance ready for execution.
PermutationParameterFactory - Class in org.uma.evolver.parameter.factory: Factory class for creating and configuring categorical parameters specific to evolutionary algorithms that operate on permutation-based solutions.
PermutationParameterFactory() - Constructor for class org.uma.evolver.parameter.factory.PermutationParameterFactory
PermutationRDEMOEA - Class in org.uma.evolver.algorithm.base.rdsmoea: Implementation of RDS-MOEA for permutation problems.
PermutationRDEMOEA(int, ParameterSpace) - Constructor for class org.uma.evolver.algorithm.base.rdsmoea.PermutationRDEMOEA: Constructs an NSGAIIPermutation instance with the given population size and parameter space.
PermutationRDEMOEA(Problem<PermutationSolution<Integer>>, int, int, ParameterSpace) - Constructor for class org.uma.evolver.algorithm.base.rdsmoea.PermutationRDEMOEA: Constructs an NSGAIIPermutation instance with the given problem, population size, and maximum number of evaluations.
PermutationVariationParameter - Class in org.uma.evolver.parameter.catalogue.variationparameter: A parameter class for configuring variation operators specifically designed for permutation solutions.
PermutationVariationParameter(String, List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.variationparameter.PermutationVariationParameter: Constructs a new VariationPermutationParameter with the specified list of variation strategy names.
PermutationVariationParameter(List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.variationparameter.PermutationVariationParameter: Constructs a new VariationPermutationParameter with the specified list of variation strategy names.
PERTURBATION - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
PerturbationParameter - Class in org.uma.evolver.parameter.catalogue: A categorical parameter representing different perturbation strategies for Particle Swarm Optimization (PSO).
PerturbationParameter(String, List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.PerturbationParameter
PerturbationParameter(List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.PerturbationParameter: Creates a new PerturbationParameter with the specified valid values.
PMX - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADPermutationParameterSpace
PMX - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIPermutationParameterSpace
PMX - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEAPermutationParameterSpace
POLYNOMIAL - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADDoubleParameterSpace
POLYNOMIAL - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
POLYNOMIAL - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIDoubleParameterSpace
POLYNOMIAL - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEADoubleParameterSpace
POLYNOMIAL_MUTATION_DISTRIBUTION_INDEX - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADDoubleParameterSpace
POLYNOMIAL_MUTATION_DISTRIBUTION_INDEX - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
POLYNOMIAL_MUTATION_DISTRIBUTION_INDEX - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIDoubleParameterSpace
POLYNOMIAL_MUTATION_DISTRIBUTION_INDEX - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEADoubleParameterSpace
POPULATION - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADCommonParameterSpace
POPULATION - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIICommonParameterSpace
POPULATION - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEACommonParameterSpace
POPULATION_AND_NEIGHBORHOOD_MATING_POOL_SELECTION - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADCommonParameterSpace
POPULATION_SIZE_WITH_ARCHIVE - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIICommonParameterSpace
POPULATION_SIZE_WITH_ARCHIVE - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEACommonParameterSpace
populationSize - Variable in class org.uma.evolver.algorithm.base.moead.BaseMOEAD: The size of the population.
populationSize - Variable in class org.uma.evolver.algorithm.base.nsgaii.BaseNSGAII: The size of the population.
populationSize - Variable in class org.uma.evolver.algorithm.base.rdsmoea.BaseRDEMOEA
populationSize - Variable in class org.uma.evolver.algorithm.base.smsemoa.BaseSMSEMOA
POSITION_UPDATE - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
PositionUpdateParameter - Class in org.uma.evolver.parameter.catalogue: A categorical parameter representing different position update strategies for Particle Swarm Optimization (PSO).
PositionUpdateParameter(String, List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.PositionUpdateParameter: Constructs a new PositionUpdateParameter instance with the given name and list of update strategies.
PositionUpdateParameter(List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.PositionUpdateParameter: Creates a new PositionUpdateParameter with the specified valid values.
POWER_LAW - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADDoubleParameterSpace
POWER_LAW - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIDoubleParameterSpace
POWER_LAW_MUTATION_DELTA - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADDoubleParameterSpace
POWER_LAW_MUTATION_DELTA - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIDoubleParameterSpace
ProbabilityParameter - Class in org.uma.evolver.parameter.catalogue: A specialized DoubleParameter that represents a probability value between 0.0 and 1.0 (inclusive).
ProbabilityParameter(String) - Constructor for class org.uma.evolver.parameter.catalogue.ProbabilityParameter: Creates a new ProbabilityParameter with the specified name.
problem - Variable in class org.uma.evolver.algorithm.base.moead.BaseMOEAD: The optimization problem to be solved.
problem - Variable in class org.uma.evolver.algorithm.base.mopso.BaseMOPSO: The optimization problem to be solved.
problem - Variable in class org.uma.evolver.algorithm.base.nsgaii.BaseNSGAII: The optimization problem to be solved.
problem - Variable in class org.uma.evolver.algorithm.base.rdsmoea.BaseRDEMOEA
problem - Variable in class org.uma.evolver.algorithm.base.smsemoa.BaseSMSEMOA
ProblemFamilyInfo<S> - Interface in org.uma.evolver.util.problemfamilyinfo: Interface defining methods for returning information about problem families, including a list with their implementations, a list with the names of the reference fronts, and a list containing the typical number of evaluations used to optimize them by metaheuristics.
problemList() - Method in class org.uma.evolver.util.problemfamilyinfo.DTLZ3DProblemFamilyInfo
problemList() - Method in interface org.uma.evolver.util.problemfamilyinfo.ProblemFamilyInfo
problemList() - Method in class org.uma.evolver.util.problemfamilyinfo.RE3DProblemFamilyInfo
problemList() - Method in class org.uma.evolver.util.problemfamilyinfo.WFG2DProblemFamilyInfo
problemList() - Method in class org.uma.evolver.util.problemfamilyinfo.ZDTProblemFamilyInfo
process(String, Object, ParameterSpace) - Method in interface org.uma.evolver.parameter.yaml.ParameterProcessor: Processes a parameter and adds it to the parameter space.
process(String, Object, ParameterSpace) - Method in class org.uma.evolver.parameter.yaml.processors.CategoricalParameterProcessor: Processes a categorical parameter from YAML configuration.
process(String, Object, ParameterSpace) - Method in class org.uma.evolver.parameter.yaml.processors.DoubleParameterProcessor: Processes a double parameter from YAML configuration.
process(String, Object, ParameterSpace) - Method in class org.uma.evolver.parameter.yaml.processors.IntegerParameterProcessor: Processes an integer parameter from YAML configuration.
put(Parameter<?>) - Method in class org.uma.evolver.parameter.ParameterSpace: Adds a parameter to the parameter space.

R

RAND_1_BIN - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADDoubleParameterSpace
RAND_1_EXP - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADDoubleParameterSpace
RAND_2_BIN - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADDoubleParameterSpace
RANDOM - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADDoubleParameterSpace
RANDOM_SELECTED_VALUE - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
RANDOM_SELECTION - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
RANDOM_SELECTION - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIICommonParameterSpace
RANDOM_SELECTION - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEACommonParameterSpace
RandomRangeEvaluationsStrategy - Class in org.uma.evolver.metaoptimizationproblem.evaluationbudgetstrategy: Implementation of EvaluationBudgetStrategy that generates random evaluation counts within a specified range.
RandomRangeEvaluationsStrategy(int, int) - Constructor for class org.uma.evolver.metaoptimizationproblem.evaluationbudgetstrategy.RandomRangeEvaluationsStrategy: Creates a new RandomRangeEvaluationsStrategy with the specified range.
RandomRangeEvaluationsStrategy(int, int, Random) - Constructor for class org.uma.evolver.metaoptimizationproblem.evaluationbudgetstrategy.RandomRangeEvaluationsStrategy: Creates a new RandomRangeEvaluationsStrategy with the specified range and random seed.
RangeParameter<T> - Class in org.uma.evolver.parameter.type: A generic parameter class for numeric values constrained within an inclusive range [lowerBound, upperBound].
RangeParameter(String, T, T) - Constructor for class org.uma.evolver.parameter.type.RangeParameter: Constructs a RangeParameter with the specified name and bounds.
ranking - Variable in class org.uma.evolver.algorithm.base.nsgaii.BaseNSGAII: The ranking strategy used for non-dominated sorting of solutions.
ranking - Variable in class org.uma.evolver.algorithm.base.rdsmoea.BaseRDEMOEA
ranking - Variable in class org.uma.evolver.algorithm.base.smsemoa.BaseSMSEMOA
RANKING - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEACommonParameterSpace
RANKING_AND_DENSITY_ESTIMATOR - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEACommonParameterSpace
rankingAndCrowdingComparator - Variable in class org.uma.evolver.algorithm.base.nsgaii.BaseNSGAII: Comparator that combines ranking and crowding distance for solution comparison.
rankingAndCrowdingComparator - Variable in class org.uma.evolver.algorithm.base.rdsmoea.BaseRDEMOEA
RankingParameter<S> - Class in org.uma.evolver.parameter.catalogue: A categorical parameter representing different ranking strategies for solutions in multi-objective optimization.
RankingParameter(String, List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.RankingParameter: Creates a new RankingParameter with the specified name and valid ranking strategies.
RankingParameter(List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.RankingParameter: Creates a new RankingParameter with the specified valid ranking strategies.
RDEMOEA_NSGAII_ZDT4Example - Class in org.uma.evolver.example.base
RDEMOEA_NSGAII_ZDT4Example() - Constructor for class org.uma.evolver.example.base.RDEMOEA_NSGAII_ZDT4Example
RDEMOEA_SPEA2_DTLZ2Example - Class in org.uma.evolver.example.base
RDEMOEA_SPEA2_DTLZ2Example() - Constructor for class org.uma.evolver.example.base.RDEMOEA_SPEA2_DTLZ2Example
RDEMOEACommonParameterSpace<S> - Class in org.uma.evolver.algorithm.base.rdsmoea.parameterspace: Abstract parameter space for RDS-MOEA (Ranking and Density Selection Multi-Objective Evolutionary Algorithm) variants.
RDEMOEACommonParameterSpace() - Constructor for class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEACommonParameterSpace
RDEMOEADoubleParameterSpace - Class in org.uma.evolver.algorithm.base.rdsmoea.parameterspace: Parameter space for RDS-MOEA with double-encoded solutions.
RDEMOEADoubleParameterSpace() - Constructor for class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEADoubleParameterSpace
RDEMOEAPermutationParameterSpace - Class in org.uma.evolver.algorithm.base.rdsmoea.parameterspace: Parameter space for NSGA-II algorithm variants using permutation-based solutions.
RDEMOEAPermutationParameterSpace() - Constructor for class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEAPermutationParameterSpace
RE3DProblemFamilyInfo - Class in org.uma.evolver.util.problemfamilyinfo: Class implementing the interface ProblemFamilyInfo for the RE problems having three objective functions.
RE3DProblemFamilyInfo() - Constructor for class org.uma.evolver.util.problemfamilyinfo.RE3DProblemFamilyInfo
referenceFronts() - Method in class org.uma.evolver.util.problemfamilyinfo.DTLZ3DProblemFamilyInfo
referenceFronts() - Method in interface org.uma.evolver.util.problemfamilyinfo.ProblemFamilyInfo
referenceFronts() - Method in class org.uma.evolver.util.problemfamilyinfo.RE3DProblemFamilyInfo
referenceFronts() - Method in class org.uma.evolver.util.problemfamilyinfo.WFG2DProblemFamilyInfo
referenceFronts() - Method in class org.uma.evolver.util.problemfamilyinfo.ZDTProblemFamilyInfo
register(String, Function<List<String>, CategoricalParameter>) - Method in class org.uma.evolver.parameter.factory.DoubleParameterFactory: Registers a parameter creator for a specific parameter type.
REMOVAL_POLICY - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEACommonParameterSpace
REPAIR_BOUNDS - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
REPAIR_BOUNDS - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIDoubleParameterSpace
REPAIR_BOUNDS - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEADoubleParameterSpace
REPAIR_RANDOM - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
REPAIR_RANDOM - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIDoubleParameterSpace
REPAIR_RANDOM - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEADoubleParameterSpace
REPAIR_ROUND - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
REPAIR_ROUND - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIDoubleParameterSpace
REPAIR_ROUND - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEADoubleParameterSpace
RepairDoubleSolutionStrategyParameter - Class in org.uma.evolver.parameter.catalogue: A categorical parameter representing different repair strategies for double-solution variables that fall outside their defined bounds.
RepairDoubleSolutionStrategyParameter(String, List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.RepairDoubleSolutionStrategyParameter: Creates a new RepairDoubleSolutionStrategyParameter with the specified name and repair strategies.
RepairDoubleSolutionStrategyParameter(List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.RepairDoubleSolutionStrategyParameter: Creates a new RepairDoubleSolutionStrategyParameter with the specified repair strategies.
REPLACEMENT - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEACommonParameterSpace
ReplacementParameter<S> - Class in org.uma.evolver.parameter.catalogue: A categorical parameter representing different replacement strategies in evolutionary algorithms.
ReplacementParameter(String, List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.ReplacementParameter: Constructs a new ReplacementParameter instance with the given name and list of selection strategies.
ReplacementParameter(List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.ReplacementParameter: Creates a new ReplacementParameter with the specified replacement strategies.
ROUND - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADDoubleParameterSpace

S

SBX - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADDoubleParameterSpace
SBX - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIDoubleParameterSpace
SBX - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEADoubleParameterSpace
SBX_DISTRIBUTION_INDEX - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADDoubleParameterSpace
SBX_DISTRIBUTION_INDEX - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIDoubleParameterSpace
SBX_DISTRIBUTION_INDEX - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEADoubleParameterSpace
SCATTER_SEARCH - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADDoubleParameterSpace
SCATTER_SEARCH - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIDoubleParameterSpace
SCATTER_SEARCH - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEADoubleParameterSpace
SCATTER_SEARCH - Static variable in class org.uma.evolver.parameter.catalogue.createinitialsolutionsparameter.CreateInitialSolutionsDoubleParameter: Strategy that creates solutions using scatter search with a reference set.
SCATTER_SEARCH_INITIALIZATION - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
SCRAMBLE - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADPermutationParameterSpace
SCRAMBLE - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIPermutationParameterSpace
SCRAMBLE - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEAPermutationParameterSpace
SELECTION - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADCommonParameterSpace
SELECTION - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIICommonParameterSpace
SELECTION - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEACommonParameterSpace
SELECTION_TOURNAMENT_SIZE - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
SELECTION_TOURNAMENT_SIZE - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIICommonParameterSpace
SELECTION_TOURNAMENT_SIZE - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEACommonParameterSpace
SelectionParameter<S> - Class in org.uma.evolver.parameter.catalogue.selectionparameter: A categorical parameter representing different selection strategies for evolutionary algorithms.
SelectionParameter(String, List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.selectionparameter.SelectionParameter: Creates a new SelectionParameter with the specified name and selection strategies.
SelectionParameter(List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.selectionparameter.SelectionParameter: Creates a new SelectionParameter with the specified selection strategies.
SequenceGeneratorParameter - Class in org.uma.evolver.parameter.catalogue: A categorical parameter representing different sequence generation strategies.
SequenceGeneratorParameter() - Constructor for class org.uma.evolver.parameter.catalogue.SequenceGeneratorParameter
SequenceGeneratorParameter(String, List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.SequenceGeneratorParameter: Creates a new SequenceGeneratorParameter with the specified name.
sequenceLength(int) - Method in class org.uma.evolver.parameter.catalogue.SequenceGeneratorParameter: Sets the length of the sequence to be generated.
SEQUENTIAL - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEACommonParameterSpace
setCrossover(CrossoverOperator<DoubleSolution>) - Method in class org.uma.evolver.algorithm.meta.MetaAsyncNSGAIIBuilder: Sets the crossover operator to be used by the algorithm.
setDensityEstimator(DensityEstimator<S>) - Method in class org.uma.evolver.parameter.catalogue.ReplacementParameter: Sets the density estimator to be used by the replacement operator.
setMaxEvaluations(int) - Method in class org.uma.evolver.algorithm.meta.MetaAsyncNSGAIIBuilder: Sets the maximum number of evaluations for the algorithm.
setMaxEvaluations(int) - Method in class org.uma.evolver.algorithm.meta.MetaNSGAIIBuilder: Sets the maximum number of evaluations for the NSGA-II algorithm.
setMaxEvaluations(int) - Method in class org.uma.evolver.algorithm.meta.MetaSMPSOBuilder: Sets the maximum number of evaluations for the SMPSO algorithm.
setMutation(MutationOperator<DoubleSolution>) - Method in class org.uma.evolver.algorithm.meta.MetaAsyncNSGAIIBuilder: Sets the mutation operator to be used by the algorithm.
setMutationProbabilityFactor(double) - Method in class org.uma.evolver.algorithm.meta.MetaNSGAIIBuilder: Sets the mutation probability factor for the NSGA-II algorithm.
setNonConfigurableParameters() - Method in class org.uma.evolver.algorithm.base.moead.BaseMOEAD: Configures any parameters that are fixed or derived from the problem instance.
setNonConfigurableParameters() - Method in class org.uma.evolver.algorithm.base.moead.BinaryMOEAD: Sets non-configurable parameters that depend on the problem or algorithm configuration.
setNonConfigurableParameters() - Method in class org.uma.evolver.algorithm.base.moead.DoubleMOEAD: Sets non-configurable parameters that depend on the problem or algorithm configuration.
setNonConfigurableParameters() - Method in class org.uma.evolver.algorithm.base.moead.PermutationMOEAD: Sets non-configurable parameters that depend on the problem or algorithm configuration.
setNonConfigurableParameters() - Method in class org.uma.evolver.algorithm.base.mopso.BaseMOPSO: Configures non-configurable parameters based on the problem's characteristics.
setNonConfigurableParameters() - Method in class org.uma.evolver.algorithm.base.nsgaii.BaseNSGAII: Configures any parameters that are fixed or derived from the problem instance.
setNonConfigurableParameters() - Method in class org.uma.evolver.algorithm.base.nsgaii.BinaryNSGAII: Configures non-configurable parameters based on the problem's characteristics.
setNonConfigurableParameters() - Method in class org.uma.evolver.algorithm.base.nsgaii.DoubleNSGAII: Configures non-configurable parameters based on the problem's characteristics.
setNonConfigurableParameters() - Method in class org.uma.evolver.algorithm.base.nsgaii.PermutationNSGAII: Configures non-configurable parameters based on the problem's characteristics.
setNonConfigurableParameters() - Method in class org.uma.evolver.algorithm.base.rdsmoea.BaseRDEMOEA: Configures any parameters that are fixed or derived from the problem instance.
setNonConfigurableParameters() - Method in class org.uma.evolver.algorithm.base.rdsmoea.DoubleRDEMOEA: Sets non-configurable parameters that depend on the problem or algorithm configuration.
setNonConfigurableParameters() - Method in class org.uma.evolver.algorithm.base.rdsmoea.PermutationRDEMOEA: Sets non-configurable parameters that depend on the problem or algorithm configuration.
setNonConfigurableParameters() - Method in class org.uma.evolver.algorithm.base.smsemoa.BaseSMSEMOA: Configures any parameters that are fixed or derived from the problem instance.
setNonConfigurableParameters() - Method in class org.uma.evolver.algorithm.base.smsemoa.DoubleSMSEMOA: Configures non-configurable parameters that depend on the problem or algorithm configuration.
setNumberOfCores(int) - Method in class org.uma.evolver.algorithm.meta.MetaAsyncNSGAIIBuilder: Sets the number of CPU cores to use for parallel evaluation.
setNumberOfCores(int) - Method in class org.uma.evolver.algorithm.meta.MetaNSGAIIBuilder: Sets the number of cores to use for parallel evaluation.
setNumberOfCores(int) - Method in class org.uma.evolver.algorithm.meta.MetaSMPSOBuilder: Sets the number of cores to use for parallel evaluation.
setNumberOfEvaluations(int) - Method in class org.uma.evolver.util.EvaluationsQualityIndicator: Sets the number of evaluations that this indicator should return.
setOffspringPopulationSize(int) - Method in class org.uma.evolver.algorithm.meta.MetaNSGAIIBuilder: Sets the offspring population size for the NSGA-II algorithm.
setParameterRelationships() - Method in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADBinaryParameterSpace
setParameterRelationships() - Method in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADCommonParameterSpace: Establishes relationships and dependencies between parameters in the MOEA/D parameter space.
setParameterRelationships() - Method in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADDoubleParameterSpace
setParameterRelationships() - Method in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADPermutationParameterSpace
setParameterRelationships() - Method in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace: Sets up relationships between parameters.
setParameterRelationships() - Method in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIBinaryParameterSpace: Establishes relationships and dependencies between parameters specific to binary-coded NSGA-II.
setParameterRelationships() - Method in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIICommonParameterSpace: Establishes relationships and dependencies between parameters in the parameter space.
setParameterRelationships() - Method in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIDoubleParameterSpace: Establishes relationships and dependencies between parameters specific to real-coded NSGA-II.
setParameterRelationships() - Method in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIPermutationParameterSpace: Establishes relationships and dependencies between parameters specific to permutation-based NSGA-II.
setParameterRelationships() - Method in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEACommonParameterSpace
setParameterRelationships() - Method in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEADoubleParameterSpace
setParameterRelationships() - Method in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEAPermutationParameterSpace: Establishes relationships and dependencies between parameters specific to permutation-based NSGA-II.
setParameterSpace() - Method in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADBinaryParameterSpace
setParameterSpace() - Method in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADCommonParameterSpace: Defines and adds all parameters to the parameter space for MOEA/D.
setParameterSpace() - Method in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADDoubleParameterSpace
setParameterSpace() - Method in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADPermutationParameterSpace
setParameterSpace() - Method in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace: Initializes all parameters in the parameter space.
setParameterSpace() - Method in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIBinaryParameterSpace: Defines and adds all parameters specific to binary-coded NSGA-II to the parameter space.
setParameterSpace() - Method in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIICommonParameterSpace: Defines and adds all common parameters to the parameter space for NSGA-II variants.
setParameterSpace() - Method in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIDoubleParameterSpace: Defines and adds all parameters specific to real-coded NSGA-II to the parameter space.
setParameterSpace() - Method in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIPermutationParameterSpace: Defines and adds all parameters specific to permutation-based NSGA-II to the parameter space.
setParameterSpace() - Method in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEACommonParameterSpace
setParameterSpace() - Method in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEADoubleParameterSpace
setParameterSpace() - Method in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEAPermutationParameterSpace: Defines and adds all parameters specific to permutation-based NSGA-II to the parameter space.
setPopulationSize(int) - Method in class org.uma.evolver.algorithm.meta.MetaAsyncNSGAIIBuilder: Sets the population size for the asynchronous NSGA-II algorithm.
setPopulationSize(int) - Method in class org.uma.evolver.algorithm.meta.MetaNSGAIIBuilder: Sets the population size for the NSGA-II algorithm.
setRanking(Ranking<S>) - Method in class org.uma.evolver.parameter.catalogue.ReplacementParameter: Sets the ranking strategy to be used by the replacement operator.
setSize(int) - Method in class org.uma.evolver.parameter.catalogue.ExternalArchiveParameter: Sets the maximum size of the external archive.
setSwarmSize(int) - Method in class org.uma.evolver.algorithm.meta.MetaSMPSOBuilder: Sets the swarm size for the SMPSO algorithm.
setTopLevelParameters() - Method in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADCommonParameterSpace: Identifies and adds the top-level parameters for MOEA/D.
setTopLevelParameters() - Method in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace: Identifies and adds the top-level parameters to the list.
setTopLevelParameters() - Method in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIICommonParameterSpace: Identifies and adds the top-level parameters to the list.
setTopLevelParameters() - Method in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEACommonParameterSpace
SIMPLE_INVERSION - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADPermutationParameterSpace
SIMPLE_INVERSION - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIPermutationParameterSpace
SIMPLE_INVERSION - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEAPermutationParameterSpace
SINGLE_POINT_CROSSOVER - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADBinaryParameterSpace
SINGLE_POINT_CROSSOVER - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIBinaryParameterSpace
SMPSOOptimizingNSGAIIForProblemRE31 - Class in org.uma.evolver.example.meta: Class for running SMPSO as meta-optimizer to configure DoubleNSGAII using problem RE31 as training set.
SMPSOOptimizingNSGAIIForProblemRE31() - Constructor for class org.uma.evolver.example.meta.SMPSOOptimizingNSGAIIForProblemRE31
SMSEMOAExample - Class in org.uma.evolver.example.base
SMSEMOAExample() - Constructor for class org.uma.evolver.example.base.SMSEMOAExample
SPATIAL_SPREAD_DEVIATION_ARCHIVE - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
SPSO2007_VELOCITY_INITIALIZATION - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
SPSO2011_VELOCITY_INITIALIZATION - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
SPSO2011_VELOCITY_UPDATE - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
STRENGTH_RANKING - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEACommonParameterSpace
StringParameter - Class in org.uma.evolver.parameter.type
StringParameter(String) - Constructor for class org.uma.evolver.parameter.type.StringParameter
SUB_PROBLEM_ID_GENERATOR - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADCommonParameterSpace
subProblemIdGenerator - Variable in class org.uma.evolver.algorithm.base.moead.BaseMOEAD: Generator for subproblem indices.
SWAP - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADPermutationParameterSpace
SWAP - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIPermutationParameterSpace
SWAP - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEAPermutationParameterSpace
SWARM_INITIALIZATION - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
SWARM_SIZE - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
swarmSize - Variable in class org.uma.evolver.algorithm.base.mopso.BaseMOPSO: The size of the particle swarm.

T

topLevelParameters - Variable in class org.uma.evolver.parameter.ParameterSpace
topLevelParameters() - Method in class org.uma.evolver.parameter.ParameterSpace: Returns an unmodifiable list of top-level parameters in this parameter space.
toString() - Method in class org.uma.evolver.parameter.ConditionalParameter: Returns a string representation of this conditional parameter.
toString() - Method in class org.uma.evolver.parameter.Parameter: Returns a string representation of this parameter, including its value and sub-parameters.
toString() - Method in class org.uma.evolver.parameter.type.BooleanParameter: Returns a formatted string representation of this parameter, including sub-parameters if any.
toString() - Method in class org.uma.evolver.parameter.type.CategoricalIntegerParameter: Returns a formatted string representation of this parameter including name, value, and valid values.
toString() - Method in class org.uma.evolver.parameter.type.CategoricalParameter: Returns a formatted string representation of this parameter including name, value, and valid values.
toString() - Method in class org.uma.evolver.parameter.type.RangeParameter: Returns a string representation of the parameter including name, value, and bounds.
toString() - Method in class org.uma.evolver.util.WriteExecutionDataToFilesObserver
TOURNAMENT - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIICommonParameterSpace
TOURNAMENT - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEACommonParameterSpace
TOURNAMENT_SELECTION - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
TSCHEBYSCHEFF - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADCommonParameterSpace

U

UNBOUNDED_ARCHIVE - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADCommonParameterSpace
UNBOUNDED_ARCHIVE - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
UNBOUNDED_ARCHIVE - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIICommonParameterSpace
UNBOUNDED_ARCHIVE - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEACommonParameterSpace
UNDC - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADDoubleParameterSpace
UNIFORM - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADDoubleParameterSpace
UNIFORM - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
UNIFORM - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIDoubleParameterSpace
UNIFORM - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEADoubleParameterSpace
UNIFORM_CROSSOVER - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADBinaryParameterSpace
UNIFORM_CROSSOVER - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIBinaryParameterSpace
UNIFORM_MUTATION_PERTURBATION - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADDoubleParameterSpace
UNIFORM_MUTATION_PERTURBATION - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
UNIFORM_MUTATION_PERTURBATION - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIDoubleParameterSpace
UNIFORM_MUTATION_PERTURBATION - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEADoubleParameterSpace
update(Observable<Map<String, Object>>, Map<String, Object>) - Method in class org.uma.evolver.util.WriteExecutionDataToFilesObserver: This method gets the population
updateEvaluations(int) - Method in class org.uma.evolver.util.OutputResults
upperBound - Variable in class org.uma.evolver.parameter.type.RangeParameter: Inclusive upper bound of the parameter.
Usage Example - Search tag in class org.uma.evolver.algorithm.base.moead.BinaryMOEAD: Section
Usage Example - Search tag in class org.uma.evolver.algorithm.base.moead.DoubleMOEAD: Section
Usage Example - Search tag in class org.uma.evolver.algorithm.base.moead.PermutationMOEAD: Section

V

validate(int) - Method in interface org.uma.evolver.metaoptimizationproblem.evaluationbudgetstrategy.EvaluationBudgetStrategy: Validates the configuration of the evaluation budget strategy against the number of problems.
validate(int) - Method in class org.uma.evolver.metaoptimizationproblem.evaluationbudgetstrategy.FixedEvaluationsStrategy
validate(int) - Method in class org.uma.evolver.metaoptimizationproblem.evaluationbudgetstrategy.RandomRangeEvaluationsStrategy
validator - Variable in class org.uma.evolver.parameter.type.RangeParameter: Predicate used to validate whether the parameter's value is within range.
validValues() - Method in class org.uma.evolver.parameter.type.CategoricalIntegerParameter: Returns the list of valid values for this parameter.
validValues() - Method in class org.uma.evolver.parameter.type.CategoricalParameter: Returns the list of valid values for this parameter.
value() - Method in class org.uma.evolver.parameter.Parameter: Returns the current value of this parameter.
value(T) - Method in class org.uma.evolver.parameter.Parameter: Sets the value of this parameter.
VARIATION - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADCommonParameterSpace
VARIATION - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIICommonParameterSpace
VARIATION - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEACommonParameterSpace
VariationParameter<S> - Class in org.uma.evolver.parameter.catalogue.variationparameter: Abstract parameter class representing a configurable variation operator in evolutionary algorithms.
VariationParameter(String, List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.variationparameter.VariationParameter: Constructs a new VariationParameter with the specified name and list of variation strategy names.
VariationParameter(List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.variationparameter.VariationParameter: Constructs a new VariationParameter with the specified list of variation strategy names.
VELOCITY_CHANGE_WHEN_LOWER_LIMIT_IS_REACHED - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
VELOCITY_CHANGE_WHEN_UPPER_LIMIT_IS_REACHED - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
VELOCITY_INITIALIZATION - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
VELOCITY_UPDATE - Static variable in class org.uma.evolver.algorithm.base.mopso.MOPSOParameterSpace
VelocityInitializationParameter - Class in org.uma.evolver.parameter.catalogue: A categorical parameter representing different velocity initialization strategies for Particle Swarm Optimization (PSO).
VelocityInitializationParameter(String, List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.VelocityInitializationParameter
VelocityInitializationParameter(List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.VelocityInitializationParameter: Creates a new VelocityInitializationParameter with the specified valid values.
VelocityUpdateParameter - Class in org.uma.evolver.parameter.catalogue: A categorical parameter representing different velocity update strategies for Particle Swarm Optimization (PSO).
VelocityUpdateParameter(String, List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.VelocityUpdateParameter: Creates a new VelocityUpdateParameter with the specified name and valid values.
VelocityUpdateParameter(List<String>) - Constructor for class org.uma.evolver.parameter.catalogue.VelocityUpdateParameter: Creates a new VelocityUpdateParameter with the specified valid values.

W

WEIGHTED_SUM - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADCommonParameterSpace
weightVectorFilesDirectory - Variable in class org.uma.evolver.algorithm.base.moead.BaseMOEAD: Directory containing the weight vector files.
WFG2DProblemFamilyInfo - Class in org.uma.evolver.util.problemfamilyinfo
WFG2DProblemFamilyInfo() - Constructor for class org.uma.evolver.util.problemfamilyinfo.WFG2DProblemFamilyInfo
WHOLE_ARITHMETIC - Static variable in class org.uma.evolver.algorithm.base.moead.parameterspace.MOEADDoubleParameterSpace
WHOLE_ARITHMETIC - Static variable in class org.uma.evolver.algorithm.base.nsgaii.parameterspace.NSGAIIDoubleParameterSpace
WHOLE_ARITHMETIC - Static variable in class org.uma.evolver.algorithm.base.rdsmoea.parameterspace.RDEMOEADoubleParameterSpace
writeDecodedSolutionsFoFile(List<Parameter<?>>, List<DoubleSolution>, String) - Static method in class org.uma.evolver.parameter.ParameterManagement
writeDecodedSolutionsToDoubleValuesFoFile(List<Parameter<?>>, List<DoubleSolution>, String) - Static method in class org.uma.evolver.parameter.ParameterManagement
WriteExecutionDataToFilesObserver - Class in org.uma.evolver.util: This observer stores a solution list in files.
WriteExecutionDataToFilesObserver(int, OutputResults) - Constructor for class org.uma.evolver.util.WriteExecutionDataToFilesObserver: Constructor
writeResultsToFiles(List<DoubleSolution>) - Method in class org.uma.evolver.util.OutputResults

Y

YAMLParameterSpace - Class in org.uma.evolver.parameter.yaml: A YAML-based parameter space implementation that loads multi-objective metaheuristic parameter configurations from YAML files.
YAMLParameterSpace(String, ParameterFactory<?>) - Constructor for class org.uma.evolver.parameter.yaml.YAMLParameterSpace: Constructs a new YAMLParameterSpace by loading parameters from the specified YAML file.

Z

ZDTProblemFamilyInfo - Class in org.uma.evolver.util.problemfamilyinfo
ZDTProblemFamilyInfo() - Constructor for class org.uma.evolver.util.problemfamilyinfo.ZDTProblemFamilyInfo

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