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.NoMutation;
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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.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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                if ((i+1) < b.length) sb.append(separator);
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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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        	System.err.println("error in AbstractEAIndividual::getDefaultDataString: type " + individual.getClass() + " not implemented");
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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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    //private double                          m_MyuRatio                  = 6;
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    private int                             m_Mu                       = 5;
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    private int                             m_Lambda                    = 20;
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    private boolean                         m_UsePlusStrategy           = false;
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    private Population                      m_Population                = new Population();
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    private InterfaceOptimizationProblem    m_Problem                   = new B1Problem();
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	protected int                             m_Mu                       = 5;
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	protected int                             m_Lambda                    = 20;
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	protected boolean                         m_UsePlusStrategy           = false;
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    protected Population                      m_Population                = new Population();
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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_PartnerSelection          = new SelectRandom();
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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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     * @param population The population that is to be evaluated
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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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        population.incrGeneration();
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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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//    }
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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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     */
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    protected Population generateEvalChildren(Population fromPopulation) {
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