CBN should now also work with (m+l)-ES

src/javaeva/server/go/operators/postprocess/PostProcess.java

@@ -321,14 +321,16 @@ public class PostProcess {
 	 * @param maxSteps
 	 * @param fixedStepSize
 	 */
-	public static void processWithHC(Population pop, AbstractOptimizationProblem problem, int maxSteps, double fixedStepSize) {
+	public static int processWithHC(Population pop, AbstractOptimizationProblem problem, int maxSteps, double fixedStepSize) {
 //		pop.SetFunctionCalls(0); // or else optimization wont restart on an "old" population
 //		pop.setGenerationTo(0);
+		int stepsBef = pop.getFunctionCalls();
 		processWithHC(pop, problem, new EvaluationTerminator(pop.getFunctionCalls()+maxSteps), new MutateESFixedStepSize(fixedStepSize));
+		return pop.getFunctionCalls()-stepsBef;
 	}
 	
-	public static void processWithHC(Population pop, AbstractOptimizationProblem problem, int maxSteps) {
+	public static int processWithHC(Population pop, AbstractOptimizationProblem problem, int maxSteps) {
-		processWithHC(pop, problem, maxSteps, defaultMutationStepSize);
+		return processWithHC(pop, problem, maxSteps, defaultMutationStepSize);
 	}
 	/**
 	 * Optimize a population with a default hill-climbing heuristic with a given termination criterion and mutation operator.
@@ -504,8 +506,8 @@ public class PostProcess {
 			} else clusteredPop = inputPop;
 			
 			if (params.getPostProcessSteps() > 0) {
-				processWithHC(clusteredPop, problem, params.getPostProcessSteps());
+				int stepsDone = processWithHC(clusteredPop, problem, params.getPostProcessSteps());
-				if (listener != null) listener.println("HC post processing: " + params.getPostProcessSteps() + " steps done.");
+				if (listener != null) listener.println("HC post processing: " + stepsDone + " steps done.");
 				// some individuals may have now converged again
 				if (params.getPostProcessClusterSigma() > 0) {
 					// so if wished, cluster again.

src/javaeva/server/go/strategies/ClusterBasedNichingEA.java

@@ -307,22 +307,30 @@ public class ClusterBasedNichingEA implements InterfacePopulationChangedEventLis
 //    	m_Optimizer.initByPopulation(species, false);
     	if (m_Optimizer instanceof EvolutionStrategies) {
     		EvolutionStrategies es = (EvolutionStrategies)m_Optimizer;
-    		int mu = (int)(muLambdaRatio*species.size());
+    		int mu = Math.max(1,(int)(muLambdaRatio*species.size()));
-    		if (mu < 1) mu = 1;
+    		if (mu >= species.size()) {
-    		else if (mu >= species.size()) {
     			if (TRACE) System.err.println("warning, muLambdaRatio produced mu >= lambda.. reducing to mu=lambda-1");
     			mu = species.size() - 1;
     		}
     		es.setMu(mu);
     		es.setLambda(species.size());
+    		if (TRACE) System.out.println("mu: "+es.getMu() + " / lambda: " + es.getLambda());
     	}
     	if (TRACE) {
-    		System.out.println("spec size: " +  species.size() + ", says its " + species.getPopulationSize());
+    		System.out.println("Bef: spec size: " + species.size() + ", says its " + species.getPopulationSize());
     		System.out.println("Best bef: " + BeanInspector.toString(m_Optimizer.getPopulation().getBestFitness()));
     	}
     	this.m_Optimizer.optimize();
-		if (TRACE) System.out.println("Best aft: " + BeanInspector.toString(m_Optimizer.getPopulation().getBestFitness()));
+    	Population retPop =  m_Optimizer.getPopulation();
-    	return m_Optimizer.getPopulation();
+		if (TRACE) {
+			System.out.println("Aft: spec size: " + retPop.size() + ", says its " + retPop.getPopulationSize());
+			System.out.println("Best aft: " + BeanInspector.toString(retPop.getBestFitness()));
+		}
+    	if (retPop.size() != retPop.getPopulationSize()) {
+    		if (TRACE) System.out.println("correcting popsize after opt: " + retPop.getPopulationSize() + " to " + retPop.size());
+    		retPop.setPopulationSize(retPop.size());
+    	}
+    	return retPop;
     }
     
     public void optimize() {

src/javaeva/server/go/strategies/EvolutionStrategies.java

@@ -39,7 +39,9 @@ public class EvolutionStrategies implements InterfaceOptimizer, java.io.Serializ
     private InterfaceSelection              m_PartnerSelection          = new SelectRandom();
     private InterfaceSelection              m_EnvironmentSelection      = new SelectBestIndividuals();
     private int                             m_NumberOfPartners          = 1;
+    private int								origPopSize					= -1; // especially for CBN
     private double[]                        m_FitnessOfParents          = null;
+    private boolean							forceOrigPopSize			= true;// especially for CBN
 
     transient private String                m_Identifier = "";
     transient private InterfacePopulationChangedEventListener m_Listener;
@@ -75,14 +77,14 @@ public class EvolutionStrategies implements InterfaceOptimizer, java.io.Serializ
     public void init() {
         // @todo In case of CBN-ES i need to read the population size!?
         // @todo but how!? I guess this will never do...
-        int orgPopSize = this.m_Population.getPopulationSize();
+//        int orgPopSize = this.m_Population.getPopulationSize();
-        if (this.m_InitialPopulationSize > orgPopSize) {
+//        if (this.m_InitialPopulationSize > orgPopSize) {
-            this.m_Population.setPopulationSize(this.m_InitialPopulationSize);
+//            this.m_Population.setPopulationSize(this.m_InitialPopulationSize);
-        }
+//        }
         //System.out.println("init");
         this.m_Problem.initPopulation(this.m_Population);
         this.evaluatePopulation(this.m_Population);
-        this.m_Population.setPopulationSize(orgPopSize);
+//        this.m_Population.setPopulationSize(orgPopSize);
         this.firePropertyChangedEvent("NextGenerationPerformed");
 //        int myu         = this.m_Population.getPopulationSize();
 //        int initPopSize = 0;
@@ -101,6 +103,8 @@ public class EvolutionStrategies implements InterfaceOptimizer, java.io.Serializ
      * @param reset     If true the population is reset.
      */
     public void initByPopulation(Population pop, boolean reset) {
+    	origPopSize = pop.getPopulationSize();
+//    	System.out.println("ES: orig popsize is " + origPopSize);
         this.m_Population = (Population)pop.clone();
         if (reset) this.m_Population.init();
         this.evaluatePopulation(this.m_Population);
@@ -181,11 +185,14 @@ public class EvolutionStrategies implements InterfaceOptimizer, java.io.Serializ
 ////            System.out.println("Population Strategy: ("+ this.m_Myu+","+this.m_Lambda+")");
 //        }
        //System.out.println("optimize");
+        
         // first perform the environment selection to select myu parents
         this.m_EnvironmentSelection.prepareSelection(this.m_Population);
         parents = this.m_EnvironmentSelection.selectFrom(this.m_Population, this.m_Mu);
         this.m_Population.clear();
         this.m_Population.addPopulation(parents);
+        
+        
         // now generate the lambda offsprings
         this.m_FitnessOfParents = null;
         nextGeneration = this.generateChildren();
@@ -199,7 +206,21 @@ public class EvolutionStrategies implements InterfaceOptimizer, java.io.Serializ
             this.applySuccessRule((rate/((double)this.m_FitnessOfParents.length)), this.m_Population, nextGeneration);
         }
         if (this.m_UsePlusStrategy) nextGeneration.addPopulation(this.m_Population);
-        this.m_Population = nextGeneration;
+        
+        if (forceOrigPopSize && (origPopSize > 0) && (origPopSize < nextGeneration.size())) {
+        	// this is especially for CBN: 
+        	this.m_EnvironmentSelection.prepareSelection(nextGeneration);
+        	Population tmpPop = (Population)nextGeneration.clone();
+            nextGeneration.clear();
+            nextGeneration.addPopulation(this.m_EnvironmentSelection.selectFrom(tmpPop, origPopSize));
+//            System.out.println("ES post selection! " + origPopSize + " from " + tmpPop.size());
+            m_Population = nextGeneration;
+        } else {
+        	if ((origPopSize > 0) && (origPopSize != nextGeneration.size())) {
+        		System.err.println("Warning in ES! orig: " + origPopSize + " / " + nextGeneration.size());
+        	}
+        	this.m_Population = nextGeneration;
+        }
         //System.out.println("Population size: " + this.m_Population.size());
         //System.out.println("-- Best Fitness " + this.m_Population.getBestFitness()[0]);
         
@@ -208,7 +229,7 @@ public class EvolutionStrategies implements InterfaceOptimizer, java.io.Serializ
 
     /** This method is just a shortcut to set the mutation step size for
      * all individuals of these two populations for the 1/5 Success rule.
-     * This is only necessary because i decieded to make the variable
+     * This is only necessary because i decided to make the variable
      * non static
      * @param successRate   The success rate
      * @param oldPop        The old population
@@ -353,6 +374,8 @@ public class EvolutionStrategies implements InterfaceOptimizer, java.io.Serializ
         return this.m_Population;
     }
     public void setPopulation(Population pop){
+    	origPopSize = pop.size();
+//    	System.out.println("ES: orig popsize is " + origPopSize);
         this.m_Population = pop;
     }
     public String populationTipText() {