Package org.uma.jmetal.util

Class SolutionListUtils

java.lang.Object

org.uma.jmetal.util.SolutionListUtils

public class SolutionListUtils
extends Object

Author:

Antonio J. Nebro

Constructor Summary

Constructors

Constructor	Description
SolutionListUtils()

Method Summary

Modifier and Type	Method	Description
static <S extends Solution<?>> List<S>	distanceBasedSubsetSelection(List<S> originalSolutionList, int finalListSize)	Method implements a version of the distance-based subset selection algorithm described in: H.
static <S extends Solution<?>> double[][]	distanceMatrix(List<S> solutionSet)	Returns a matrix with the euclidean distance between each pair of solutions in the population.
static <S> void	fillPopulationWithNewSolutions(List<S> solutionList, Problem<S> problem, int maxListSize)	Fills a population with new solutions until its size is maxListSize
static <S> S	findBestSolution(List<S> solutionList, Comparator<S> comparator)
static <S> int	findIndexOfBestSolution(List<S> solutionList, Comparator<S> comparator)	Finds the index of the best solution in the list according to a comparator
static <S> int	findIndexOfWorstSolution(List<? extends S> solutionList, Comparator<S> comparator)	Finds the index of the worst solution in the list according to a comparator
<S> S	findWorstSolution(Collection<S> solutionList, Comparator<S> comparator)
static <S extends Solution<?>> List<S>	getInvertedFront(List<S> solutionSet)	This method receives a normalized list of non-dominated solutions and return the inverted one.
static <S extends Solution<?>> double[][]	getMatrixWithObjectiveValues(List<S> solutionList)	Given a list of solutions, returns a matrix with the objective values of all the solutions
static <S extends Solution<?>> List<S>	getNonDominatedSolutions(List<S> solutionList)
static <S extends Solution<?>> double[]	getObjectiveArrayFromSolutionList(List<S> solutionList, int objective)	Given a solution list and the identifier of an objective (0, 1, etc), returns an array with the values of that objective in all the solutions of the list
static <S extends Solution<?>> boolean	isSolutionDominatedBySolutionList(S solution, List<? extends S> solutionSet)
static <S extends Solution<?>> double[][]	normalizedDistanceMatrix(List<S> solutionSet, double[] maxs, double[] mins)
static <S extends Solution<?>> List<S>	normalizeSolutionList(List<S> solutions)	This method receives a list of non-dominated solutions and maximum and minimum values of the objectives, and returns a normalized set of solutions.
static <S extends Solution<?>> List<S>	normalizeSolutionList(List<S> solutions, double[] minValues, double[] maxValues)	This method receives a list of non-dominated solutions and maximum and minimum values of the objectives, and returns a normalized set of solutions.
static <S> void	removeSolutionsFromList(List<S> solutionList, int numberOfSolutionsToRemove)	Removes a number of solutions from a list
static <S> void	restart(List<S> solutionList, Problem<S> problem, int percentageOfSolutionsToRemove)	This method takes a list of solutions, removes a percentage of its solutions, and it is filled with new random generated solutions
static <S extends Solution<?>> double[][]	writeObjectivesToMatrix(List<S> solutionList)

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Details

SolutionListUtils

public SolutionListUtils()

Method Details

getNonDominatedSolutions

public static <S extends Solution<?>> List<S> getNonDominatedSolutions(List<S> solutionList)

findWorstSolution

public <S> S findWorstSolution(Collection<S> solutionList,
 Comparator<S> comparator)

findIndexOfBestSolution

public static <S> int findIndexOfBestSolution(List<S> solutionList,
 Comparator<S> comparator)

Finds the index of the best solution in the list according to a comparator

Parameters:

solutionList -

comparator -

Returns:

The index of the best solution

findIndexOfWorstSolution

public static <S> int findIndexOfWorstSolution(List<? extends S> solutionList,
 Comparator<S> comparator)

Finds the index of the worst solution in the list according to a comparator

Parameters:

solutionList -

comparator -

Returns:

The index of the best solution

findBestSolution

public static <S> S findBestSolution(List<S> solutionList,
 Comparator<S> comparator)

writeObjectivesToMatrix

public static <S extends Solution<?>> double[][] writeObjectivesToMatrix(List<S> solutionList)

normalizeSolutionList

public static <S extends Solution<?>> List<S> normalizeSolutionList(List<S> solutions,
 double[] minValues,
 double[] maxValues)

This method receives a list of non-dominated solutions and maximum and minimum values of the objectives, and returns a normalized set of solutions.

Parameters:

solutions - A list of non-dominated solutions

minValues - The minimum values of the objectives

maxValues - The maximum values of the objectives

Returns:

the normalized list of non-dominated solutions

normalizeSolutionList

public static <S extends Solution<?>> List<S> normalizeSolutionList(List<S> solutions)

This method receives a list of non-dominated solutions and maximum and minimum values of the objectives, and returns a normalized set of solutions.

Parameters:

solutions - A list of non-dominated solutions

Returns:

the normalized list of non-dominated solutions

getInvertedFront

public static <S extends Solution<?>> List<S> getInvertedFront(List<S> solutionSet)

This method receives a normalized list of non-dominated solutions and return the inverted one. This operation is needed for minimization problem

Parameters:

solutionSet - The front to invert

Returns:

The inverted front

isSolutionDominatedBySolutionList

public static <S extends Solution<?>> boolean isSolutionDominatedBySolutionList(S solution,
 List<? extends S> solutionSet)

distanceMatrix

public static <S extends Solution<?>> double[][] distanceMatrix(List<S> solutionSet)

Returns a matrix with the euclidean distance between each pair of solutions in the population. Distances are measured in the objective space

Parameters:

solutionSet -

Returns:

normalizedDistanceMatrix

public static <S extends Solution<?>> double[][] normalizedDistanceMatrix(List<S> solutionSet,
 double[] maxs,
 double[] mins)

restart

public static <S> void restart(List<S> solutionList,
 Problem<S> problem,
 int percentageOfSolutionsToRemove)

This method takes a list of solutions, removes a percentage of its solutions, and it is filled with new random generated solutions

Parameters:

solutionList -

problem -

percentageOfSolutionsToRemove -

removeSolutionsFromList

public static <S> void removeSolutionsFromList(List<S> solutionList,
 int numberOfSolutionsToRemove)

Removes a number of solutions from a list

Parameters:

solutionList - The list of solutions

numberOfSolutionsToRemove -

fillPopulationWithNewSolutions

public static <S> void fillPopulationWithNewSolutions(List<S> solutionList,
 Problem<S> problem,
 int maxListSize)

Fills a population with new solutions until its size is maxListSize

Type Parameters:

S - The type of the solutions to be created

Parameters:

solutionList - The list of solutions

problem - The problem being solved

maxListSize - The target size of the list

getObjectiveArrayFromSolutionList

public static <S extends Solution<?>> double[] getObjectiveArrayFromSolutionList(List<S> solutionList,
 int objective)

Given a solution list and the identifier of an objective (0, 1, etc), returns an array with the values of that objective in all the solutions of the list

Type Parameters:

S -

Parameters:

solutionList -

objective -

Returns:

distanceBasedSubsetSelection

public static <S extends Solution<?>> List<S> distanceBasedSubsetSelection(List<S> originalSolutionList,
 int finalListSize)

Method implements a version of the distance-based subset selection algorithm described in: H. K. Singh, K. S. Bhattacharjee, and T. Ray, ‘Distance-based subset selection for benchmarking in evolutionary multi/many-objective optimization,’ IEEE Trans. on Evolutionary Computation, 23(5), 904-912, (2019). DOI: https://doi.org/10.1109/TEVC.2018.2883094

Type Parameters:

S -

Parameters:

originalSolutionList -

finalListSize - The size of the result list

Returns:

getMatrixWithObjectiveValues

public static <S extends Solution<?>> double[][] getMatrixWithObjectiveValues(List<S> solutionList)

Given a list of solutions, returns a matrix with the objective values of all the solutions

Type Parameters:

S -

Parameters:

solutionList -

Returns: