Minor visibility changes to ES.
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@ -16,7 +16,6 @@ import eva2.server.go.operators.crossover.NoCrossover;
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import eva2.server.go.operators.mutation.InterfaceMutation;
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import eva2.server.go.operators.mutation.InterfaceMutation;
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import eva2.server.go.operators.mutation.NoMutation;
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import eva2.server.go.operators.mutation.NoMutation;
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import eva2.server.go.populations.Population;
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import eva2.server.go.populations.Population;
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import eva2.server.go.problems.AbstractOptimizationProblem;
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import eva2.server.go.problems.InterfaceOptimizationProblem;
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import eva2.server.go.problems.InterfaceOptimizationProblem;
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import eva2.tools.EVAERROR;
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import eva2.tools.EVAERROR;
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@ -913,6 +912,9 @@ public abstract class AbstractEAIndividual implements IndividualInterface, java.
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sb.append(b[i].getStringRepresentation());
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sb.append(b[i].getStringRepresentation());
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if ((i+1) < b.length) sb.append(separator);
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if ((i+1) < b.length) sb.append(separator);
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}
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}
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} else if (BeanInspector.hasMethod(individual, "toString") != null) {
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EVAERROR.errorMsgOnce("warning in AbstractEAIndividual::getDefaultDataString: type " + individual.getClass() + " has no default data representation, using toString...");
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return individual.toString();
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} else {
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} else {
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System.err.println("error in AbstractEAIndividual::getDefaultDataString: type " + individual.getClass() + " not implemented");
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System.err.println("error in AbstractEAIndividual::getDefaultDataString: type " + individual.getClass() + " not implemented");
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}
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}
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@ -34,11 +34,11 @@ import eva2.server.go.problems.InterfaceOptimizationProblem;
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public class EvolutionStrategies implements InterfaceOptimizer, java.io.Serializable {
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public class EvolutionStrategies implements InterfaceOptimizer, java.io.Serializable {
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//private double m_MyuRatio = 6;
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//private double m_MyuRatio = 6;
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private int m_Mu = 5;
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protected int m_Mu = 5;
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private int m_Lambda = 20;
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protected int m_Lambda = 20;
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private boolean m_UsePlusStrategy = false;
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protected boolean m_UsePlusStrategy = false;
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private Population m_Population = new Population();
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protected Population m_Population = new Population();
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private InterfaceOptimizationProblem m_Problem = new B1Problem();
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protected InterfaceOptimizationProblem m_Problem = new B1Problem();
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private InterfaceSelection m_ParentSelection = new SelectRandom();
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private InterfaceSelection m_ParentSelection = new SelectRandom();
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private InterfaceSelection m_PartnerSelection = new SelectRandom();
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private InterfaceSelection m_PartnerSelection = new SelectRandom();
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private InterfaceSelection m_EnvironmentSelection = new SelectBestIndividuals();
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private InterfaceSelection m_EnvironmentSelection = new SelectBestIndividuals();
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@ -125,7 +125,7 @@ public class EvolutionStrategies implements InterfaceOptimizer, java.io.Serializ
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* given problem.
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* given problem.
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* @param population The population that is to be evaluated
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* @param population The population that is to be evaluated
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*/
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*/
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private void evaluatePopulation(Population population) {
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protected void evaluatePopulation(Population population) {
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this.m_Problem.evaluate(population);
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this.m_Problem.evaluate(population);
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population.incrGeneration();
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population.incrGeneration();
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}
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}
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@ -144,7 +144,8 @@ public class EvolutionStrategies implements InterfaceOptimizer, java.io.Serializ
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// else this.m_Population.setPopulationSize(lambda);
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// else this.m_Population.setPopulationSize(lambda);
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// }
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// }
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/** This method will generate the offspring population from the
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/**
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* This method will generate the offspring population from the
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* given population of evaluated individuals.
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* given population of evaluated individuals.
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*/
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*/
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protected Population generateEvalChildren(Population fromPopulation) {
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protected Population generateEvalChildren(Population fromPopulation) {
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