org.uma.jmetal.util

Class SolutionListUtils

java.lang.Object

org.uma.jmetal.util.SolutionListUtils

public class SolutionListUtils
extends Object

Created by Antonio J. Nebro on 04/10/14. Modified by Juanjo 13/03/15

Constructor Summary

Constructors

Constructor and Description
SolutionListUtils()

Method Summary

Modifier and Type	Method and Description
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 Solution	findBestSolution(List<? extends Solution> solutionList, Comparator<Solution> comparator)
static int	findIndexOfBestSolution(List<? extends Solution> solutionList, Comparator<Solution> comparator) Finds the index of the best solution in the list according to a comparator
static int	findIndexOfWorstSolution(List<? extends Solution> solutionList, Comparator<Solution> comparator) Finds the index of the worst solution in the list according to a comparator
int	findWorstSolution(List<? extends Solution> solutionList, Comparator<Solution> 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 List<Double>	getMaximumValues(List<Solution> solutionList) Gets the maximum values for each objectives in a given list of solutions
static List<Double>	getMinimumValues(List<Solution> solutionList) Gets the minimum values for each objectives in a given list of solutions
static <S extends Solution> List<S>	getNondominatedSolutions(List<S> solutionList)
static List<Solution>	getNormalizedFront(List<Solution> solutionList, List<Double> maximumValue, List<Double> minimumValue) This method receives a list of non-dominated solutions and maximum and minimum values of the objectives, and returns a the normalized set of solutions.
static <S extends Solution> boolean	isSolutionDominatedBySolutionList(S solution, List<S> solutionSet)
static <S extends Solution> List<S>	selectNRandomDifferentSolutions(int numberOfSolutionsToBeReturned, List<S> solutionList) This method receives a normalized list of non-dominated solutions and return the inverted one.
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 Detail

SolutionListUtils

public SolutionListUtils()

Method Detail

getNondominatedSolutions

public static <S extends Solution> List<S> getNondominatedSolutions(List<S> solutionList)

findWorstSolution

public int findWorstSolution(List<? extends Solution> solutionList,
                             Comparator<Solution> comparator)

findIndexOfBestSolution

public static int findIndexOfBestSolution(List<? extends Solution> solutionList,
                                          Comparator<Solution> 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 int findIndexOfWorstSolution(List<? extends Solution> solutionList,
                                           Comparator<Solution> 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 Solution findBestSolution(List<? extends Solution> solutionList,
                                        Comparator<Solution> comparator)

writeObjectivesToMatrix

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

getMaximumValues

public static List<Double> getMaximumValues(List<Solution> solutionList)

Gets the maximum values for each objectives in a given list of solutions

Parameters:

solutionList - The list of solutions

Returns:

A list with the maximum values for each objective

getMinimumValues

public static List<Double> getMinimumValues(List<Solution> solutionList)

Gets the minimum values for each objectives in a given list of solutions

Parameters:

solutionList - The list of solutions

Returns:

A list with the minimum values for each objective

getNormalizedFront

public static List<Solution> getNormalizedFront(List<Solution> solutionList,
                                                List<Double> maximumValue,
                                                List<Double> minimumValue)

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

Parameters:

solutionList - A list of non-dominated solutions

maximumValue - The maximum values of the objectives

minimumValue - The minimum values of the objectives

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<S> solutionSet)

selectNRandomDifferentSolutions

public static <S extends Solution> List<S> selectNRandomDifferentSolutions(int numberOfSolutionsToBeReturned,
                                                                           List<S> solutionList)

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

Parameters:

solutionList - The front to invert

Returns:

The inverted front

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: