Minor crossover updates
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@ -7,6 +7,11 @@ import eva2.server.go.problems.InterfaceOptimizationProblem;
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import eva2.tools.math.RNG;
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import eva2.tools.math.RNG;
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/**
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/**
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* The children are randomized intermediate combinations of the parents,
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* namely c[i]=Sum_j (r_i * p_ji)
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* where r_i are uniform random numbers normed to the sum of one and
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* p_ji is the i-th component of parent j.
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*
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* Created by IntelliJ IDEA.
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* Created by IntelliJ IDEA.
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* User: streiche
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* User: streiche
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* Date: 25.07.2003
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* Date: 25.07.2003
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@ -75,7 +80,7 @@ public class CrossoverESArithmetical implements InterfaceCrossover, java.io.Seri
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// write the result back
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// write the result back
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for (int i = 0; i < result.length; i++) ((InterfaceESIndividual)result[i]).SetDGenotype(children[i]);
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for (int i = 0; i < result.length; i++) ((InterfaceESIndividual)result[i]).SetDGenotype(children[i]);
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}
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}
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//in case the crossover was successfull lets give the mutation operators a chance to mate the strategy parameters
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//in case the crossover was successful lets give the mutation operators a chance to mate the strategy parameters
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for (int i = 0; i < result.length; i++) result[i].getMutationOperator().crossoverOnStrategyParameters(indy1, partners);
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for (int i = 0; i < result.length; i++) result[i].getMutationOperator().crossoverOnStrategyParameters(indy1, partners);
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//for (int i = 0; i < result.length; i++) System.out.println("After Crossover: " +result[i].getSolutionRepresentationFor());
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//for (int i = 0; i < result.length; i++) System.out.println("After Crossover: " +result[i].getSolutionRepresentationFor());
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return result;
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return result;
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@ -1,9 +1,6 @@
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package eva2.server.go.operators.crossover;
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package eva2.server.go.operators.crossover;
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import javax.swing.*;
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import eva2.gui.Plot;
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import eva2.server.go.individuals.AbstractEAIndividual;
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import eva2.server.go.individuals.AbstractEAIndividual;
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import eva2.server.go.individuals.InterfaceESIndividual;
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import eva2.server.go.individuals.InterfaceESIndividual;
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import eva2.server.go.populations.Population;
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import eva2.server.go.populations.Population;
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@ -11,6 +8,13 @@ import eva2.server.go.problems.InterfaceOptimizationProblem;
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import eva2.tools.math.RNG;
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import eva2.tools.math.RNG;
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/**
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/**
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* The flat crossover inits values randomly within the extreme values of
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* all parents, namely
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* c[i]=rand(min_j(p_ij), max_j(p_ij)).
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*
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* where c[i] is the i-th child component and p_ij is the i-th component
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* of parent j.
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*
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* Created by IntelliJ IDEA.
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* Created by IntelliJ IDEA.
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* User: streiche
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* User: streiche
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* Date: 02.12.2003
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* Date: 02.12.2003
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