Cleanup.
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@@ -727,10 +727,6 @@ public class BinaryScatterSearch extends AbstractOptimizer implements java.io.Se
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this.refSetSize = pop.getTargetSize();
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this.refSetSize = pop.getTargetSize();
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}
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}
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public String populationTipText() {
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return "The Population";
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}
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@Override
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@Override
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public InterfaceSolutionSet getAllSolutions() {
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public InterfaceSolutionSet getAllSolutions() {
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return new SolutionSet(this.refSet);
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return new SolutionSet(this.refSet);
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@@ -261,10 +261,6 @@ public class ClusteringHillClimbing implements InterfacePopulationChangedEventLi
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this.population = pop;
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this.population = pop;
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}
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}
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public String populationTipText() {
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return "Change the number of starting individuals stored (Cluster-HC).";
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}
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@Override
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@Override
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public InterfaceSolutionSet getAllSolutions() {
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public InterfaceSolutionSet getAllSolutions() {
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Population tmp = new Population();
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Population tmp = new Population();
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@@ -689,11 +689,6 @@ public class DifferentialEvolution extends AbstractOptimizer implements java.io.
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return "Differential Evolution";
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return "Differential Evolution";
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}
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}
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public String populationTipText() {
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return "Edit the properties of the population used.";
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}
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@Override
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@Override
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public InterfaceSolutionSet getAllSolutions() {
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public InterfaceSolutionSet getAllSolutions() {
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return new SolutionSet(this.population);
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return new SolutionSet(this.population);
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@@ -138,11 +138,6 @@ public class EvolutionaryProgramming extends AbstractOptimizer implements java.i
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return "EP";
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return "EP";
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}
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}
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public String populationTipText() {
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return "Edit the properties of the population used.";
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}
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@Override
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@Override
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public InterfaceSolutionSet getAllSolutions() {
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public InterfaceSolutionSet getAllSolutions() {
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return new SolutionSet(getPopulation());
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return new SolutionSet(getPopulation());
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@@ -9,6 +9,7 @@ import eva2.optimization.population.SolutionSet;
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import eva2.problems.B1Problem;
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import eva2.problems.B1Problem;
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import eva2.problems.InterfaceOptimizationProblem;
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import eva2.problems.InterfaceOptimizationProblem;
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import eva2.util.annotation.Description;
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import eva2.util.annotation.Description;
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import eva2.util.annotation.Parameter;
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/**
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/**
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* The flood algorithm, and alternative to the threshold algorithms. No really
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* The flood algorithm, and alternative to the threshold algorithms. No really
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@@ -26,6 +27,8 @@ public class FloodAlgorithm extends AbstractOptimizer implements java.io.Seriali
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private int fitnessCallsNeeded = 0;
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private int fitnessCallsNeeded = 0;
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GAIndividualBinaryData bestIndividual, testIndividual;
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GAIndividualBinaryData bestIndividual, testIndividual;
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public double initialFloodPeak = 2000.0, currentFloodPeak;
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public double initialFloodPeak = 2000.0, currentFloodPeak;
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@Parameter(name = "drainRate", description = "Set the drain rate that reduces the current flood level each generation.")
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public double drainRate = 1.0;
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public double drainRate = 1.0;
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public FloodAlgorithm() {
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public FloodAlgorithm() {
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@@ -193,17 +196,13 @@ public class FloodAlgorithm extends AbstractOptimizer implements java.io.Seriali
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return "MS-FA";
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return "MS-FA";
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}
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}
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public String populationTipText() {
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return "Change the number of best individuals stored (MS-FA).";
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}
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@Override
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@Override
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public InterfaceSolutionSet getAllSolutions() {
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public InterfaceSolutionSet getAllSolutions() {
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return new SolutionSet(getPopulation());
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return new SolutionSet(getPopulation());
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}
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}
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/**
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/**
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* This methods allow you to set/get the temperatur of the flood algorithm
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* This methods allow you to set/get the temperature of the flood algorithm
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* procedure
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* procedure
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*
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*
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* @return The initial flood level.
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* @return The initial flood level.
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@@ -236,8 +235,4 @@ public class FloodAlgorithm extends AbstractOptimizer implements java.io.Seriali
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this.drainRate = 0.0;
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this.drainRate = 0.0;
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}
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}
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}
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}
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public String drainRateTipText() {
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return "Set the drain rate that reduces the current flood level each generation.";
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}
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}
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}
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@@ -139,8 +139,4 @@ public class HillClimbing extends AbstractOptimizer implements java.io.Serializa
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public InterfaceSolutionSet getAllSolutions() {
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public InterfaceSolutionSet getAllSolutions() {
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return new SolutionSet(getPopulation());
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return new SolutionSet(getPopulation());
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}
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}
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public String populationTipText() {
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return "Change the number of best individuals stored (MS-HC).";
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}
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}
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}
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@@ -250,10 +250,6 @@ public class MemeticAlgorithm implements InterfaceOptimizer, java.io.Serializabl
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this.globalOptimizer.setPopulation(pop);
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this.globalOptimizer.setPopulation(pop);
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}
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}
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public String populationTipText() {
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return "Edit the properties of the population used.";
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}
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/**
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/**
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* Choose the global optimization strategy to use
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* Choose the global optimization strategy to use
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*
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*
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@@ -242,10 +242,6 @@ public class MultiObjectiveEA implements InterfaceOptimizer, java.io.Serializabl
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this.optimizer.setPopulation(pop);
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this.optimizer.setPopulation(pop);
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}
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}
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public String populationTipText() {
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return "Edit the properties of the Population used.";
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}
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@Override
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@Override
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public InterfaceSolutionSet getAllSolutions() {
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public InterfaceSolutionSet getAllSolutions() {
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return new SolutionSet(getPopulation(), ArchivingNSGAII.getNonDominatedSortedFront(getPopulation().getArchive()).getSortedPop(new EAIndividualComparator(0)));
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return new SolutionSet(getPopulation(), ArchivingNSGAII.getNonDominatedSortedFront(getPopulation().getArchive()).getSortedPop(new EAIndividualComparator(0)));
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@@ -144,11 +144,6 @@ public class SteadyStateGA extends AbstractOptimizer implements java.io.Serializ
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return "SS-GA";
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return "SS-GA";
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}
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}
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public String populationTipText() {
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return "Edit the properties of the population used.";
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}
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@Override
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@Override
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public InterfaceSolutionSet getAllSolutions() {
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public InterfaceSolutionSet getAllSolutions() {
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return new SolutionSet(getPopulation());
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return new SolutionSet(getPopulation());
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