org.uma.jmetal.util.artificialdecisionmaker.impl

Class ArtificialDecisionMakerDecisionTree<S extends Solution<?>>

java.lang.Object

org.uma.jmetal.util.artificialdecisionmaker.ArtificialDecisionMaker<S,List<S>>

org.uma.jmetal.util.artificialdecisionmaker.impl.ArtificialDecisionMakerDecisionTree<S>

All Implemented Interfaces:

Serializable, Runnable, Algorithm<List<S>>, DescribedEntity

public class ArtificialDecisionMakerDecisionTree<S extends Solution<?>>
extends ArtificialDecisionMaker<S,List<S>>

Class implementing the Towards automatic testing of reference point based interactive methods described in: Ojalehto, V., Podkopaev, D., & Miettinen, K. (2016, September). Towards automatic testing of reference point based interactive methods. In International Conference on Parallel Problem Solving from Nature (pp. 483-492). Springer, Cham.

Author:

Cristobal Barba

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
protected List<Double>	allReferencePoints
protected List<Double>	asp
protected double	considerationProbability
protected List<Double>	currentReferencePoint
protected List<Double>	distances
protected int	evaluations
protected List<Double>	idealOjectiveVector
protected int	maxEvaluations
protected List<Double>	nadirObjectiveVector
protected int	numberOfObjectives
protected JMetalRandom	random
protected List<Double>	rankingCoeficient
protected double	tolerance
protected double	varyingProbability

Fields inherited from class org.uma.jmetal.util.artificialdecisionmaker.ArtificialDecisionMaker

algorithm, indexOfRelevantObjectiveFunctions, paretoOptimalSolutions, problem

Constructor Summary

Constructors

Constructor and Description
ArtificialDecisionMakerDecisionTree(Problem<S> problem, InteractiveAlgorithm<S,List<S>> algorithm, double considerationProbability, double tolerance, int maxEvaluations, List<Double> rankingCoeficient, List<Double> asp)

Method Summary

Modifier and Type	Method and Description
protected List<Double>	calculateReferencePoints(List<Integer> indexOfRelevantObjectiveFunctions, List<S> front, List<S> paretoOptimalSolutions)
protected List<Double>	generatePreferenceInformation()
List<Double>	getDistances()
List<Double>	getReferencePoints()
protected void	initProgress()
protected boolean	isStoppingConditionReached()
protected List<Integer>	relevantObjectiveFunctions(List<S> front)
protected void	updateParetoOptimal(List<S> front, List<S> paretoOptimalSolutions)
protected void	updateProgress()

Methods inherited from class org.uma.jmetal.util.artificialdecisionmaker.ArtificialDecisionMaker

getDescription, getName, getResult, run

Methods inherited from class java.lang.Object

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

Field Detail

idealOjectiveVector

protected List<Double> idealOjectiveVector

nadirObjectiveVector

protected List<Double> nadirObjectiveVector

rankingCoeficient

protected List<Double> rankingCoeficient

asp

protected List<Double> asp

tolerance

protected double tolerance

random

protected JMetalRandom random

considerationProbability

protected double considerationProbability

numberOfObjectives

protected int numberOfObjectives

varyingProbability

protected double varyingProbability

evaluations

protected int evaluations

maxEvaluations

protected int maxEvaluations

allReferencePoints

protected List<Double> allReferencePoints

currentReferencePoint

protected List<Double> currentReferencePoint

distances

protected List<Double> distances

Constructor Detail

ArtificialDecisionMakerDecisionTree

public ArtificialDecisionMakerDecisionTree(Problem<S> problem,
                                           InteractiveAlgorithm<S,List<S>> algorithm,
                                           double considerationProbability,
                                           double tolerance,
                                           int maxEvaluations,
                                           List<Double> rankingCoeficient,
                                           List<Double> asp)

Method Detail

generatePreferenceInformation

protected List<Double> generatePreferenceInformation()

Specified by:

generatePreferenceInformation in class ArtificialDecisionMaker<S extends Solution<?>,List<S extends Solution<?>>>

isStoppingConditionReached

protected boolean isStoppingConditionReached()

Specified by:

isStoppingConditionReached in class ArtificialDecisionMaker<S extends Solution<?>,List<S extends Solution<?>>>

initProgress

protected void initProgress()

Specified by:

initProgress in class ArtificialDecisionMaker<S extends Solution<?>,List<S extends Solution<?>>>

updateProgress

protected void updateProgress()

Specified by:

updateProgress in class ArtificialDecisionMaker<S extends Solution<?>,List<S extends Solution<?>>>

relevantObjectiveFunctions

protected List<Integer> relevantObjectiveFunctions(List<S> front)

Specified by:

relevantObjectiveFunctions in class ArtificialDecisionMaker<S extends Solution<?>,List<S extends Solution<?>>>

calculateReferencePoints

protected List<Double> calculateReferencePoints(List<Integer> indexOfRelevantObjectiveFunctions,
                                                List<S> front,
                                                List<S> paretoOptimalSolutions)

Specified by:

calculateReferencePoints in class ArtificialDecisionMaker<S extends Solution<?>,List<S extends Solution<?>>>

updateParetoOptimal

protected void updateParetoOptimal(List<S> front,
                                   List<S> paretoOptimalSolutions)

Specified by:

updateParetoOptimal in class ArtificialDecisionMaker<S extends Solution<?>,List<S extends Solution<?>>>

getReferencePoints

public List<Double> getReferencePoints()

Specified by:

getReferencePoints in class ArtificialDecisionMaker<S extends Solution<?>,List<S extends Solution<?>>>

getDistances

public List<Double> getDistances()

Specified by:

getDistances in class ArtificialDecisionMaker<S extends Solution<?>,List<S extends Solution<?>>>