All Classes
| Class | Description |
|---|---|
| AsynchronousCellularGeneticAlgorithmBinaryExample |
Class to configure and run an asynchronous cellular genetic algorithm to solve a
DoubleProblem |
| AsynchronousCellularGeneticAlgorithmExample |
Class to configure and run an asynchronous cellular genetic algorithm to solve a
DoubleProblem |
| AsynchronousCellularGeneticAlgorithmUsingAPermutationSequenceGeneratorExample |
Class to configure and run an asynchronous cellular genetic algorithm to solve a
DoubleProblem |
| BinaryTournamentGlobalBestSelection | |
| ConstantValueStrategy | |
| ConstrainedVelocityUpdate |
Method implementing a constrained velocity update.
|
| CrossoverAndMutationVariation<S extends Solution<?>> | |
| DefaultGlobalBestInitialization | |
| DefaultGlobalBestUpdate | |
| DefaultLocalBestInitialization | |
| DefaultLocalBestUpdate | |
| DefaultPositionUpdate | |
| DefaultVelocityInitialization |
Class that initializes the velocity of the particles to 0.0
|
| DefaultVelocityUpdate |
Method implementing the standard velocity PSO update strategy
|
| DifferentialEvolutionCrossoverVariation | |
| DifferentialEvolutionSelection | |
| Evaluation<S extends Solution<?>> |
Interface representing entities that evaluate a list of solutions
|
| EvolutionaryAlgorithm<S extends Solution<?>> |
Template for evolutionary algorithms.
|
| FrequencySelectionMutationBasedPerturbation |
This perturbation applies a mutation operator to a fixed set of solutions according to a
frequency parameter.
|
| GenerationalGeneticAlgorithmBinaryExample |
Class to configure and run a generational genetic algorithm to solve a
BinaryProblem |
| GenerationalGeneticAlgorithmExample |
Class to configure and run a generational genetic algorithm to solve a
DoubleProblem |
| GenerationalGeneticAlgorithmWithFitnessObserverExample |
Class to configure and run a generational genetic algorithm to solve a
DoubleProblem |
| GenerationalGeneticAlgorithmWithMultiThreadedEvaluatorExample |
Class to configure and run a generational genetic algorithm to solve a
DoubleProblem |
| GeneticAlgorithmBuilder<S extends Solution<?>> |
Class to configure and build an instance of a genetic algorithm
|
| GeneticAlgorithmTSPExample |
Class to configure and run a genetic algorithm to solve an instance of the TSP
|
| GlobalBestInitialization | |
| GlobalBestSelection | |
| GlobalBestUpdate | |
| GNSGAIIExample |
Class to configure and run the NSGA-II algorithm using a
GDominanceComparator, which
allows empower NSGA-II with a preference articulation mechanism based on reference point. |
| InertiaWeightComputingStrategy | |
| InertiaWeightRangeBasedComputingStrategy | |
| LatinHypercubeSamplingSolutionsCreation | |
| LinearDecreasingStrategy | |
| LinearIncreasingStrategy | |
| LocalBestInitialization |
TODO: comment the interface
|
| LocalBestUpdate | |
| MOEADBuilder<S extends Solution<?>> |
Class to configure and build an instance of the MOEA/D algorithm
|
| MOEADDEBuilder |
Class to configure and build an instance of the MOEA/D-DE algorithm
|
| MOEADDEDefaultConfigurationExample |
Class to configure and run the NSGA-II algorithm configured with standard settings.
|
| MOEADDefaultConfigurationExample |
Class to configure and run the NSGA-II algorithm configured with standard settings.
|
| MOEADReplacement<S extends Solution<?>> | |
| MOEADSolvingProblemDTLZ1Example |
Class to configure and run the NSGA-II algorithm configured with standard settings.
|
| MOEADWithRealTimeChartExample |
Class to configure and run the NSGA-II algorithm configured with standard settings.
|
| MOEADWithUnboundedArchiveExample |
Class to configure and run the NSGA-II algorithm configured with standard settings.
|
| MuCommaLambdaReplacement<S extends Solution<?>> |
(mu , lambda) replacement.
|
| MultiThreadedEvaluation<S extends Solution<?>> |
Class that evaluates a list of solutions using threads.
|
| MuPlusLambdaReplacement<S extends Solution<?>> |
(mu + lambda) replacement.
|
| NaryTournamentSelection<S extends Solution<?>> | |
| NeighborhoodSelection<S extends Solution<?>> |
This class produces a mating pool composed of solutions belonging to a neighborhood.
|
| NSGAIIBinaryProblemExample |
Class to configure and run the NSGA-II algorithm configured with standard settings for solving
a binary problem (
OneZeroMax is a multi-objective variant of OneMax). |
| NSGAIIBuilder<S extends Solution<?>> |
Class to configure and build an instance of the NSGA-II algorithm
|
| NSGAIIDefaultConfigurationExample |
Class to configure and run the NSGA-II algorithm configured with standard settings.
|
| NSGAIIEbesExample |
Class to configure and run the NSGA-II algorithm showing the population while the algorithm is running
|
| NSGAIISolvingConstrainedProblemExample |
Class to configure and run the NSGA-II algorithm configured with standard settings for solving a
binary problem (
OneZeroMax is a multi-objective variant of OneMax). |
| NSGAIISteadyStateExample |
Class to configure a steady-state version of NSGA-II
|
| NSGAIISteadyStateWithRealTimeChartExample |
Class to configure a steady-state version of NSGA-II, showing the current population during
the execution of the algorithm
|
| NSGAIIStoppingByHypervolume |
Class to configure and run the NSGA-II algorithm with a stopping condition based on finding
a Pareto front approximation having a hypervolume value higher than the 95% of the hypervolume
of the reference front.
|
| NSGAIIStoppingByKeyboardExample |
Class to configure and run the NSGA-II algorithm with a stopping condition based on pressing a key.
|
| NSGAIIStoppingByTimeExample |
Class to configure and run the NSGA-II algorithm with a stopping condition based a maximum
computing time.
|
| NSGAIITSPExample |
Class to configure and run the NSGA-II algorithm to solve a bi-objective TSP.
|
| NSGAIIWithCrowdingDistanceArchiveExample |
Class to configure and run the NSGA-II algorithm configured a bounded external archive that uses
the crowding distance to remove solutions when the archive gets full.
|
| NSGAIIWithMixedSolutionEncodingExample |
Class to configure and run the NSGA-II algorithm to solve a problem having a mixed-encoding.
|
| NSGAIIWithMNDSRankingExample |
Class to configure and run the NSGA-II algorithm configured with the ranking method known as
Merge non-dominated sorting ranking (DOI: https://doi.org/10.1109/TCYB.2020.2968301)
|
| NSGAIIWithPlotly2DChartExample |
Class to configure and run the NSGA-II algorithm to solve a bi-objective problem and plotting
the result front with Plotli
|
| NSGAIIWithPlotly3DChartExample |
Class to configure and run the NSGA-II algorithm to solve three-objective problem and plotting
the result front with Plotli
|
| NSGAIIWithRealTimeChartExample |
Class to configure and run the NSGA-II algorithm showing the population while the algorithm is running
|
| NSGAIIWithSmile2DChartExample |
Class to configure and run the NSGA-II algorithm to solve a bi-objective problem and plotting
the result front with Smile (https://haifengl.github.io/)
|
| NSGAIIWithSmile3DChartExample |
Class to configure and run the NSGA-II algorithm to solve a three-objective problem and plotting
the result front with Smile (https://haifengl.github.io/)
|
| NSGAIIWithUnboundedArchiveExample |
Class to configure and run the NSGA-II algorithm using an unbounded archive that stores the
non-dominated solutions found during the search.
|
| PairwiseReplacement<S extends Solution<?>> |
Given two populations of equal size, the returned population is composed of the result of the
pairwise comparison between the solutions of both populations.
|
| ParallelNSGAIIExample |
Class to configure and run the NSGA-II algorithm using the
MultiThreadedEvaluation evaluator. |
| ParticleSwarmOptimizationAlgorithm |
Template for particle swarm optimization algorithms.
|
| Perturbation | |
| PopulationAndNeighborhoodSelection<S extends Solution<?>> |
This class allows to select N different solutions that can be taken from a solution list (i.e, population or swarm) or
from a neighborhood according to a given probability.
|
| PositionUpdate | |
| RandomGlobalBestSelection | |
| RandomSearchAlgorithm<S extends Solution<?>> |
Class representing a random search algorithm.
|
| RandomSearchSingleObjectiveBinaryEncodingExample |
Class to configure and run the a random search.
|
| RandomSelectedValueStrategy | |
| RandomSelection<S extends Solution<?>> |
Randomly select a number of solutions from a list, with or without replacement
|
| RandomSolutionsCreation<S extends Solution<?>> |
Class that creates a list of randomly instantiated solutions.
|
| RankingAndDensityEstimatorPreference<S> |
A preference is a list composed of a ranking and a density estimator that specifies preferences
in the selection and replacement components of an evolutionary algorithm.
|
| RankingAndDensityEstimatorReplacement<S extends Solution<?>> | |
| Replacement<S extends Solution<?>> | |
| Replacement.RemovalPolicy | |
| ScatterSearchSolutionsCreation | |
| Selection<S extends Solution<?>> | |
| SequentialEvaluation<S extends Solution<?>> |
Class that evaluates a list of solutions sequentially.
|
| SequentialEvaluationWithArchive<S extends Solution<?>> | |
| SingleSolutionReplacement<S extends Solution<?>> |
Given an offspring population composed of a single solution, this solution is compared against a particular solution
of the population given by a
SequenceGenerator object. |
| SMPSOBuilder |
Class to configure and build an instance of the SMPSO algorithm
|
| SMPSODefaultConfigurationExample | |
| SMPSOStoppingByKeyboardExample |
Class for configuring and running the SMPSO algorithm
|
| SMPSOWithPlotliyChartExample |
Class for configuring and running the SMPSO algorithm
|
| SMPSOWithRealTimeChartExample |
Class for configuring and running the SMPSO algorithm
|
| SMPSOWithUnboundedArchiveExample | |
| SMSEMOABuilder<S extends Solution<?>> |
Class to configure and build an instance of the SMS-EMOA algorithm
|
| SMSEMOADefaultConfigurationExample |
Class to configure and run the SMSEMOA algorithm
|
| SMSEMOAReplacement<S extends Solution<?>> | |
| SMSEMOAWithRealTimeChartExample |
Class to configure and run the SMSEMOA algorithm
|
| SolutionsCreation<S extends Solution<?>> |
Interface representing entities that create a list of solutions applying some strategy (e.g, random)
|
| SPS2011VelocityUpdate |
Method implementing a velocity update strategy proposed in Standard PSO 2011.
|
| SPSO2007VelocityInitialization |
Class that initializes the velocity of the particles according to the standard PSO 2007 (SPSO 2007)
Source: Maurice Clerc.
|
| SPSO2011VelocityInitialization |
Class that initializes the velocity of the particles according to the standard PSO 2011 (SPSO 2011)
Source: Maurice Clerc.
|
| SteadyStateGeneticAlgorithmDefaultConfigurationExample |
Class to configure and run a steady-stat genetic algorithm to solve a
DoubleProblem |
| SynchronousCellularGeneticAlgorithmExample |
Class to configure and run a synchronous cellular genetic algorithm to solve a
DoubleProblem |
| Termination |
This interface represents classes that check the termination condition of an algorithm.
|
| TerminationByComputingTime |
Class that allows to check the termination condition when the computing time of an algorithm
gets higher than a given threshold.
|
| TerminationByEvaluations |
Class that allows to check the termination condition based on a maximum number of indicated
evaluations.
|
| TerminationByKeyboard |
Class that allows to check the termination condition based on introducing a character by keyboard.
|
| TerminationByQualityIndicator |
Class that allows to check the termination condition when current front is above a given
percentage of the value of a quality indicator applied to a reference front.
|
| TournamentGlobalBestSelection | |
| Variation<S extends Solution<?>> | |
| VelocityInitialization |
TODO: description missing
|
| VelocityUpdate |
Interface representing velocity update strategies
|