Reorganize imports.

More refactoring.

src/eva2/OptimizerFactory.java

@@ -5,7 +5,6 @@ import eva2.optimization.enums.MutateESCrossoverTypeEnum;
 import eva2.optimization.enums.PSOTopologyEnum;
 import eva2.optimization.enums.PostProcessMethod;
 import eva2.optimization.go.InterfacePopulationChangedEventListener;
-import eva2.optimization.operator.terminators.InterfaceTerminator;
 import eva2.optimization.individuals.*;
 import eva2.optimization.modules.OptimizationParameters;
 import eva2.optimization.operator.archiving.ArchivingNSGAII;
@@ -25,6 +24,7 @@ import eva2.optimization.operator.selection.InterfaceSelection;
 import eva2.optimization.operator.selection.SelectBestIndividuals;
 import eva2.optimization.operator.terminators.CombinedTerminator;
 import eva2.optimization.operator.terminators.EvaluationTerminator;
+import eva2.optimization.operator.terminators.InterfaceTerminator;
 import eva2.optimization.population.PBILPopulation;
 import eva2.optimization.population.Population;
 import eva2.optimization.problems.AbstractOptimizationProblem;

src/eva2/OptimizerRunnable.java

@@ -2,7 +2,6 @@ package eva2;
 
 import eva2.optimization.OptimizationStateListener;
 import eva2.optimization.go.InterfaceOptimizationParameters;
-import eva2.optimization.operator.terminators.InterfaceTerminator;
 import eva2.optimization.individuals.IndividualInterface;
 import eva2.optimization.individuals.InterfaceDataTypeBinary;
 import eva2.optimization.individuals.InterfaceDataTypeDouble;
@@ -11,6 +10,7 @@ import eva2.optimization.modules.OptimizationParameters;
 import eva2.optimization.modules.Processor;
 import eva2.optimization.operator.postprocess.InterfacePostProcessParams;
 import eva2.optimization.operator.postprocess.PostProcessParams;
+import eva2.optimization.operator.terminators.InterfaceTerminator;
 import eva2.optimization.population.Population;
 import eva2.optimization.population.SolutionSet;
 import eva2.optimization.stat.*;

src/eva2/cli/Main.java

@@ -1,22 +1,21 @@
 package eva2.cli;
 
+import com.google.gson.*;
 import eva2.OptimizerFactory;
 import eva2.optimization.OptimizationStateListener;
 import eva2.optimization.enums.DETypeEnum;
 import eva2.optimization.go.InterfacePopulationChangedEventListener;
 import eva2.optimization.modules.OptimizationParameters;
 import eva2.optimization.operator.terminators.CombinedTerminator;
-import eva2.optimization.operator.terminators.EvaluationTerminator;
 import eva2.optimization.operator.terminators.FitnessValueTerminator;
 import eva2.optimization.population.Population;
 import eva2.optimization.problems.AbstractOptimizationProblem;
 import eva2.optimization.problems.AbstractProblemDouble;
-import eva2.optimization.problems.AbstractProblemDoubleOffset;
 import eva2.optimization.strategies.DifferentialEvolution;
 import eva2.optimization.strategies.InterfaceOptimizer;
-import com.google.gson.*;
 import org.apache.commons.cli.*;
 import org.reflections.Reflections;
+
 import java.lang.reflect.Modifier;
 import java.util.Arrays;
 import java.util.Map;
@@ -323,6 +322,8 @@ public class Main implements OptimizationStateListener, InterfacePopulationChang
                 opt.addOption("inertnessOrChi", true, "Inertness or Chi");
                 opt.addOption("algType", true, "Type of PSO");
 
+                break;
+            case "EvolutionStrategies":
                 break;
             default:
                 throw new Exception("Unsupported Optimizer");

src/eva2/gui/PropertyEditorProvider.java

@@ -1,8 +1,8 @@
 package eva2.gui;
 
 import eva2.gui.editor.*;
-import eva2.optimization.operator.terminators.InterfaceTerminator;
 import eva2.optimization.individuals.codings.gp.GPArea;
+import eva2.optimization.operator.terminators.InterfaceTerminator;
 import eva2.tools.SelectedTag;
 import eva2.tools.StringSelection;
 

src/eva2/gui/PropertyPanel.java

@@ -1,14 +1,4 @@
 package eva2.gui;
-/*
- * Title:        EvA2
- * Description:
- * Copyright:    Copyright (c) 2003
- * Company:      University of Tuebingen, Computer Architecture
- * @author Holger Ulmer, Felix Streichert, Hannes Planatscher
- * @version:  $Revision: 10 $
- *            $Date: 2006-01-18 11:02:22 +0100 (Wed, 18 Jan 2006) $
- *            $Author: streiche $
- */
 
 import eva2.tools.EVAHELP;
 

src/eva2/gui/PropertySheetPanel.java

@@ -1,14 +1,4 @@
 package eva2.gui;
-/*
- * Title:        EvA2
- * Description:
- * Copyright:    Copyright (c) 2003
- * Company:      University of Tuebingen, Computer Architecture
- * @author Holger Ulmer, Felix Streichert, Hannes Planatscher
- * @version:  $Revision: 319 $
- *            $Date: 2007-12-05 11:29:32 +0100 (Wed, 05 Dec 2007) $
- *            $Author: mkron $
- */
 
 import eva2.gui.editor.GenericObjectEditor;
 import eva2.tools.EVAHELP;

src/eva2/gui/plot/DataViewer.java

@@ -1,14 +1,4 @@
 package eva2.gui.plot;
-/*
- * Title:        EvA2
- * Description:
- * Copyright:    Copyright (c) 2003
- * Company:      University of Tuebingen, Computer Architecture
- * @author Holger Ulmer, Felix Streichert, Hannes Planatscher
- * @version:  $Revision: 320 $
- *            $Date: 2007-12-06 16:05:11 +0100 (Thu, 06 Dec 2007) $
- *            $Author: mkron $
- */
 
 import java.util.ArrayList;
 

src/eva2/optimization/mocco/MOCCOParameterizeGDF.java

@@ -4,10 +4,10 @@ package eva2.optimization.mocco;
 import eva2.gui.PropertyDoubleArray;
 import eva2.gui.PropertyEditorProvider;
 import eva2.gui.editor.GenericObjectEditor;
-import eva2.optimization.operator.terminators.InterfaceTerminator;
 import eva2.optimization.go.MOCCOStandalone;
 import eva2.optimization.individuals.AbstractEAIndividual;
 import eva2.optimization.operator.moso.MOSOWeightedFitness;
+import eva2.optimization.operator.terminators.InterfaceTerminator;
 import eva2.optimization.problems.AbstractMultiObjectiveOptimizationProblem;
 import eva2.optimization.problems.InterfaceMultiObjectiveDeNovoProblem;
 import eva2.optimization.problems.InterfaceOptimizationObjective;

src/eva2/optimization/mocco/MOCCOParameterizeMO.java

@@ -3,8 +3,8 @@ package eva2.optimization.mocco;
 
 import eva2.gui.PropertyEditorProvider;
 import eva2.gui.editor.GenericObjectEditor;
-import eva2.optimization.operator.terminators.InterfaceTerminator;
 import eva2.optimization.go.MOCCOStandalone;
+import eva2.optimization.operator.terminators.InterfaceTerminator;
 import eva2.optimization.population.Population;
 import eva2.optimization.strategies.GeneticAlgorithm;
 import eva2.optimization.strategies.InterfaceOptimizer;

src/eva2/optimization/mocco/MOCCOParameterizeRefPoint.java

@@ -3,10 +3,10 @@ package eva2.optimization.mocco;
 
 import eva2.gui.PropertyEditorProvider;
 import eva2.gui.editor.GenericObjectEditor;
-import eva2.optimization.operator.terminators.InterfaceTerminator;
 import eva2.optimization.go.MOCCOStandalone;
 import eva2.optimization.operator.migration.SOBestMigration;
 import eva2.optimization.operator.moso.MOSOLpMetric;
+import eva2.optimization.operator.terminators.InterfaceTerminator;
 import eva2.optimization.problems.AbstractMultiObjectiveOptimizationProblem;
 import eva2.optimization.strategies.IslandModelEA;
 import eva2.optimization.tools.AbstractObjectEditor;

src/eva2/optimization/mocco/MOCCOParameterizeSO.java

@@ -3,8 +3,8 @@ package eva2.optimization.mocco;
 
 import eva2.gui.PropertyEditorProvider;
 import eva2.gui.editor.GenericObjectEditor;
-import eva2.optimization.operator.terminators.InterfaceTerminator;
 import eva2.optimization.go.MOCCOStandalone;
+import eva2.optimization.operator.terminators.InterfaceTerminator;
 import eva2.optimization.strategies.GeneticAlgorithm;
 import eva2.optimization.strategies.InterfaceOptimizer;
 import eva2.optimization.strategies.MultiObjectiveEA;

src/eva2/optimization/mocco/MOCCOParameterizeSTEP.java

@@ -4,10 +4,10 @@ package eva2.optimization.mocco;
 import eva2.gui.PropertyDoubleArray;
 import eva2.gui.PropertyEditorProvider;
 import eva2.gui.editor.GenericObjectEditor;
-import eva2.optimization.operator.terminators.InterfaceTerminator;
 import eva2.optimization.go.MOCCOStandalone;
 import eva2.optimization.individuals.AbstractEAIndividual;
 import eva2.optimization.operator.moso.MOSOWeightedFitness;
+import eva2.optimization.operator.terminators.InterfaceTerminator;
 import eva2.optimization.problems.AbstractMultiObjectiveOptimizationProblem;
 import eva2.optimization.problems.InterfaceMultiObjectiveDeNovoProblem;
 import eva2.optimization.problems.InterfaceOptimizationObjective;

src/eva2/optimization/mocco/MOCCOParameterizeTchebycheff.java

@@ -3,10 +3,10 @@ package eva2.optimization.mocco;
 
 import eva2.gui.PropertyEditorProvider;
 import eva2.gui.editor.GenericObjectEditor;
-import eva2.optimization.operator.terminators.InterfaceTerminator;
 import eva2.optimization.go.MOCCOStandalone;
 import eva2.optimization.operator.migration.SOBestMigration;
 import eva2.optimization.operator.moso.MOSOWeightedLPTchebycheff;
+import eva2.optimization.operator.terminators.InterfaceTerminator;
 import eva2.optimization.problems.AbstractMultiObjectiveOptimizationProblem;
 import eva2.optimization.strategies.IslandModelEA;
 import eva2.optimization.tools.AbstractObjectEditor;

src/eva2/optimization/mocco/MOCCOState.java

@@ -1,9 +1,9 @@
 package eva2.optimization.mocco;
 
-import eva2.optimization.operator.terminators.InterfaceTerminator;
 import eva2.optimization.individuals.AbstractEAIndividual;
 import eva2.optimization.operator.archiving.ArchivingAllDominating;
 import eva2.optimization.operator.terminators.EvaluationTerminator;
+import eva2.optimization.operator.terminators.InterfaceTerminator;
 import eva2.optimization.population.Population;
 import eva2.optimization.problems.AbstractMultiObjectiveOptimizationProblem;
 import eva2.optimization.problems.InterfaceMultiObjectiveDeNovoProblem;

src/eva2/optimization/modules/AbstractOptimizationParameters.java

@@ -4,9 +4,9 @@ import eva2.gui.BeanInspector;
 import eva2.optimization.go.InterfaceNotifyOnInformers;
 import eva2.optimization.go.InterfaceOptimizationParameters;
 import eva2.optimization.go.InterfacePopulationChangedEventListener;
-import eva2.optimization.operator.terminators.InterfaceTerminator;
 import eva2.optimization.operator.postprocess.InterfacePostProcessParams;
 import eva2.optimization.operator.postprocess.PostProcessParams;
+import eva2.optimization.operator.terminators.InterfaceTerminator;
 import eva2.optimization.problems.InterfaceAdditionalPopulationInformer;
 import eva2.optimization.problems.InterfaceOptimizationProblem;
 import eva2.optimization.strategies.InterfaceOptimizer;

src/eva2/optimization/modules/OptimizationParameters.java

@@ -1,8 +1,8 @@
 package eva2.optimization.modules;
 
 import eva2.optimization.go.InterfaceOptimizationParameters;
-import eva2.optimization.operator.terminators.InterfaceTerminator;
 import eva2.optimization.operator.terminators.EvaluationTerminator;
+import eva2.optimization.operator.terminators.InterfaceTerminator;
 import eva2.optimization.problems.F1Problem;
 import eva2.optimization.problems.InterfaceOptimizationProblem;
 import eva2.optimization.strategies.GeneticAlgorithm;

src/eva2/optimization/modules/Processor.java

@@ -2,7 +2,10 @@ package eva2.optimization.modules;
 
 import eva2.gui.BeanInspector;
 import eva2.optimization.OptimizationStateListener;
-import eva2.optimization.go.*;
+import eva2.optimization.go.InterfaceNotifyOnInformers;
+import eva2.optimization.go.InterfaceOptimizationParameters;
+import eva2.optimization.go.InterfacePopulationChangedEventListener;
+import eva2.optimization.go.InterfaceProcessor;
 import eva2.optimization.operator.paramcontrol.ConstantParameters;
 import eva2.optimization.operator.paramcontrol.InterfaceParameterControl;
 import eva2.optimization.operator.postprocess.PostProcess;

src/eva2/optimization/modules/SAParameters.java

@@ -2,8 +2,8 @@ package eva2.optimization.modules;
 
 import eva2.optimization.go.InterfaceOptimizationParameters;
 import eva2.optimization.go.InterfacePopulationChangedEventListener;
-import eva2.optimization.operator.terminators.InterfaceTerminator;
 import eva2.optimization.operator.terminators.EvaluationTerminator;
+import eva2.optimization.operator.terminators.InterfaceTerminator;
 import eva2.optimization.population.Population;
 import eva2.optimization.problems.B1Problem;
 import eva2.optimization.problems.InterfaceOptimizationProblem;

src/eva2/optimization/operator/postprocess/PostProcess.java

@@ -7,7 +7,6 @@ import eva2.gui.plot.Plot;
 import eva2.gui.plot.TopoPlot;
 import eva2.optimization.enums.ESMutationInitialSigma;
 import eva2.optimization.enums.PostProcessMethod;
-import eva2.optimization.operator.terminators.InterfaceTerminator;
 import eva2.optimization.individuals.*;
 import eva2.optimization.modules.OptimizationParameters;
 import eva2.optimization.operator.cluster.ClusteringDensityBased;
@@ -22,6 +21,7 @@ import eva2.optimization.operator.mutation.MutateESMutativeStepSizeControl;
 import eva2.optimization.operator.mutation.MutateESRankMuCMA;
 import eva2.optimization.operator.selection.SelectBestIndividuals;
 import eva2.optimization.operator.terminators.EvaluationTerminator;
+import eva2.optimization.operator.terminators.InterfaceTerminator;
 import eva2.optimization.population.Population;
 import eva2.optimization.problems.*;
 import eva2.optimization.stat.InterfaceTextListener;

src/eva2/optimization/problems/AbstractOptimizationProblem.java

@@ -1,7 +1,6 @@
 package eva2.optimization.problems;
 
 import eva2.optimization.enums.PostProcessMethod;
-import eva2.optimization.operator.terminators.InterfaceTerminator;
 import eva2.optimization.individuals.AbstractEAIndividual;
 import eva2.optimization.individuals.InterfaceDataTypeDouble;
 import eva2.optimization.operator.cluster.ClusteringDensityBased;
@@ -16,6 +15,7 @@ import eva2.optimization.operator.postprocess.PostProcess;
 import eva2.optimization.operator.postprocess.SolutionHistogram;
 import eva2.optimization.operator.terminators.CombinedTerminator;
 import eva2.optimization.operator.terminators.EvaluationTerminator;
+import eva2.optimization.operator.terminators.InterfaceTerminator;
 import eva2.optimization.operator.terminators.PhenotypeConvergenceTerminator;
 import eva2.optimization.operator.terminators.PopulationMeasureTerminator.ChangeTypeEnum;
 import eva2.optimization.operator.terminators.PopulationMeasureTerminator.DirectionTypeEnum;

src/eva2/optimization/stat/StatisticsStandalone.java

@@ -4,7 +4,6 @@ import eva2.optimization.population.PopulationInterface;
 import eva2.optimization.problems.InterfaceAdditionalPopulationInformer;
 
 import java.io.Serializable;
-import java.net.InetAddress;
 import java.util.ArrayList;
 import java.util.List;
 

src/eva2/optimization/strategies/BOA.java

@@ -33,9 +33,6 @@ import java.util.logging.Logger;
  * Martin Pelikan, David E. Goldberg and Erick Cantu-Paz: 'BOA: The Bayesian
  * Optimization Algorithm' the works by Martin Pelikan and David E. Goldberg.
  * Genetic and Evolutionary Computation Conference (GECCO-99), pp. 525-532
- * (1999)
- *
- * @author seitz
  */
 @Description(value = "Basic implementation of the Bayesian Optimization Algorithm based on the works by Martin Pelikan and David E. Goldberg.")
 public class BOA implements InterfaceOptimizer, java.io.Serializable {

src/eva2/optimization/strategies/MonteCarloSearch.java

@@ -8,20 +8,15 @@ import eva2.optimization.population.Population;
 import eva2.optimization.population.SolutionSet;
 import eva2.optimization.problems.B1Problem;
 import eva2.optimization.problems.InterfaceOptimizationProblem;
+import eva2.util.annotation.Description;
 
 /**
  * The simple random or Monte-Carlo search, simple but useful to evaluate the
  * complexity of the search space. This implements a Random Walk Search using
  * the initialization method of the problem instance, meaning that the random
  * characteristics may be problem dependent.
- * <p/>
- * Copyright: Copyright (c) 2003 Company: University of Tuebingen, Computer
- * Architecture
- *
- * @author Felix Streichert
- * @version: $Revision: 307 $ $Date: 2007-12-04 14:31:47 +0100 (Tue, 04 Dec
- * 2007) $ $Author: mkron $
  */
+@Description("The Monte Carlo Search repeatively creates random individuals and stores the best individuals found.")
 public class MonteCarloSearch implements InterfaceOptimizer, java.io.Serializable {
 
     /**
@@ -29,24 +24,24 @@ public class MonteCarloSearch implements InterfaceOptimizer, java.io.Serializabl
      */
     private static final long serialVersionUID = -751760624411490405L;
     // These variables are necessary for the simple testcase
-    private InterfaceOptimizationProblem m_Problem = new B1Problem();
+    private InterfaceOptimizationProblem optimizationProblem = new B1Problem();
-    private int m_MultiRuns = 100;
+    private int multiRuns = 100;
-    private int m_FitnessCalls = 100;
+    private int fitnessCalls = 100;
-    private int m_FitnessCallsNeeded = 0;
+    private int fitnessCallsNeeded = 0;
-    private Population m_Population;
+    private Population population;
-    private GAIndividualBinaryData m_Best, m_Test;
+    private GAIndividualBinaryData bestIndividual;
     // These variables are necessary for the more complex LectureGUI enviroment
-    transient private String m_Identifier = "";
+    transient private String identifier = "";
-    transient private InterfacePopulationChangedEventListener m_Listener;
+    transient private InterfacePopulationChangedEventListener populationChangedEventListener;
 
     public MonteCarloSearch() {
-        this.m_Population = new Population();
+        this.population = new Population();
-        this.m_Population.setTargetSize(50);
+        this.population.setTargetSize(50);
     }
 
     public MonteCarloSearch(MonteCarloSearch a) {
-        this.m_Population = (Population) a.m_Population.clone();
+        this.population = (Population) a.population.clone();
-        this.m_Problem = (InterfaceOptimizationProblem) a.m_Problem.clone();
+        this.optimizationProblem = (InterfaceOptimizationProblem) a.optimizationProblem.clone();
     }
 
     @Override
@@ -59,8 +54,8 @@ public class MonteCarloSearch implements InterfaceOptimizer, java.io.Serializabl
      */
     @Override
     public void init() {
-        this.m_Problem.initializePopulation(this.m_Population);
+        this.optimizationProblem.initializePopulation(this.population);
-        this.m_Problem.evaluate(this.m_Population);
+        this.optimizationProblem.evaluate(this.population);
         this.firePropertyChangedEvent(Population.NEXT_GENERATION_PERFORMED);
     }
 
@@ -72,10 +67,10 @@ public class MonteCarloSearch implements InterfaceOptimizer, java.io.Serializabl
      */
     @Override
     public void initByPopulation(Population pop, boolean reset) {
-        this.m_Population = (Population) pop.clone();
+        this.population = (Population) pop.clone();
         if (reset) {
-            this.m_Population.init();
+            this.population.init();
-            this.m_Problem.evaluate(this.m_Population);
+            this.optimizationProblem.evaluate(this.population);
             this.firePropertyChangedEvent(Population.NEXT_GENERATION_PERFORMED);
         }
     }
@@ -86,22 +81,22 @@ public class MonteCarloSearch implements InterfaceOptimizer, java.io.Serializabl
      */
     @Override
     public void optimize() {
-        Population original = (Population) this.m_Population.clone();
+        Population original = (Population) this.population.clone();
 
 //        this.problem.initializePopulation(this.population);
-        for (int i = 0; i < m_Population.size(); i++) {
+        for (int i = 0; i < population.size(); i++) {
-            m_Population.getEAIndividual(i).defaultInit(null);
+            population.getEAIndividual(i).defaultInit(null);
         }
 
-        this.m_Population.setFunctionCalls(original.getFunctionCalls());
+        this.population.setFunctionCalls(original.getFunctionCalls());
-        this.m_Problem.evaluate(this.m_Population);
+        this.optimizationProblem.evaluate(this.population);
-        for (int i = 0; i < this.m_Population.size(); i++) {
+        for (int i = 0; i < this.population.size(); i++) {
-            if (((AbstractEAIndividual) original.get(i)).isDominatingDebConstraints(((AbstractEAIndividual) this.m_Population.get(i)))) {
+            if (((AbstractEAIndividual) original.get(i)).isDominatingDebConstraints(((AbstractEAIndividual) this.population.get(i)))) {
-                this.m_Population.remove(i);
+                this.population.remove(i);
-                this.m_Population.add(i, original.get(i));
+                this.population.add(i, original.get(i));
             }
         }
-        this.m_Population.incrGeneration();
+        this.population.incrGeneration();
         this.firePropertyChangedEvent(Population.NEXT_GENERATION_PERFORMED);
     }
 
@@ -112,36 +107,37 @@ public class MonteCarloSearch implements InterfaceOptimizer, java.io.Serializabl
      */
     @Override
     public void setProblem(InterfaceOptimizationProblem problem) {
-        this.m_Problem = problem;
+        this.optimizationProblem = problem;
     }
 
     @Override
     public InterfaceOptimizationProblem getProblem() {
-        return this.m_Problem;
+        return this.optimizationProblem;
     }
 
     /**
      * This method will init the HillClimber
      */
     public void defaultInit() {
-        this.m_FitnessCallsNeeded = 0;
+        this.fitnessCallsNeeded = 0;
-        this.m_Best = new GAIndividualBinaryData();
+        this.bestIndividual = new GAIndividualBinaryData();
-        this.m_Best.defaultInit(m_Problem);
+        this.bestIndividual.defaultInit(optimizationProblem);
     }
 
     /**
      * This method will optimize
      */
     public void defaultOptimize() {
-        for (int i = 0; i < m_FitnessCalls; i++) {
+        GAIndividualBinaryData testIndividial;
-            this.m_Test = new GAIndividualBinaryData();
+        for (int i = 0; i < fitnessCalls; i++) {
-            this.m_Test.defaultInit(m_Problem);
+            testIndividial = new GAIndividualBinaryData();
-            if (this.m_Test.defaultEvaulateAsMiniBits() < this.m_Best.defaultEvaulateAsMiniBits()) {
+            testIndividial.defaultInit(optimizationProblem);
-                this.m_Best = this.m_Test;
+            if (testIndividial.defaultEvaulateAsMiniBits() < this.bestIndividual.defaultEvaulateAsMiniBits()) {
+                this.bestIndividual = testIndividial;
             }
-            this.m_FitnessCallsNeeded = i;
+            this.fitnessCallsNeeded = i;
-            if (this.m_Best.defaultEvaulateAsMiniBits() == 0) {
+            if (this.bestIndividual.defaultEvaulateAsMiniBits() == 0) {
-                i = this.m_FitnessCalls + 1;
+                i = this.fitnessCalls + 1;
             }
         }
     }
@@ -154,15 +150,15 @@ public class MonteCarloSearch implements InterfaceOptimizer, java.io.Serializabl
     public static void main(String[] args) {
         MonteCarloSearch program = new MonteCarloSearch();
         int TmpMeanCalls = 0, TmpMeanFitness = 0;
-        for (int i = 0; i < program.m_MultiRuns; i++) {
+        for (int i = 0; i < program.multiRuns; i++) {
             program.defaultInit();
             program.defaultOptimize();
-            TmpMeanCalls += program.m_FitnessCallsNeeded;
+            TmpMeanCalls += program.fitnessCallsNeeded;
-            TmpMeanFitness += program.m_Best.defaultEvaulateAsMiniBits();
+            TmpMeanFitness += program.bestIndividual.defaultEvaulateAsMiniBits();
         }
-        TmpMeanCalls /= program.m_MultiRuns;
+        TmpMeanCalls /= program.multiRuns;
-        TmpMeanFitness /= program.m_MultiRuns;
+        TmpMeanFitness /= program.multiRuns;
-        System.out.println("(" + program.m_MultiRuns + "/" + program.m_FitnessCalls + ") Mean Fitness : " + TmpMeanFitness + " Mean Calls needed: " + TmpMeanCalls);
+        System.out.println("(" + program.multiRuns + "/" + program.fitnessCalls + ") Mean Fitness : " + TmpMeanFitness + " Mean Calls needed: " + TmpMeanCalls);
     }
 
     /**
@@ -172,14 +168,14 @@ public class MonteCarloSearch implements InterfaceOptimizer, java.io.Serializabl
      */
     @Override
     public void addPopulationChangedEventListener(InterfacePopulationChangedEventListener ea) {
-        this.m_Listener = ea;
+        this.populationChangedEventListener = ea;
     }
 
     @Override
     public boolean removePopulationChangedEventListener(
             InterfacePopulationChangedEventListener ea) {
-        if (m_Listener == ea) {
+        if (populationChangedEventListener == ea) {
-            m_Listener = null;
+            populationChangedEventListener = null;
             return true;
         } else {
             return false;
@@ -190,8 +186,8 @@ public class MonteCarloSearch implements InterfaceOptimizer, java.io.Serializabl
      * Something has changed
      */
     protected void firePropertyChangedEvent(String name) {
-        if (this.m_Listener != null) {
+        if (this.populationChangedEventListener != null) {
-            this.m_Listener.registerPopulationStateChanged(this, name);
+            this.populationChangedEventListener.registerPopulationStateChanged(this, name);
         }
     }
 
@@ -206,8 +202,8 @@ public class MonteCarloSearch implements InterfaceOptimizer, java.io.Serializabl
         String result = "";
         result += "Monte-Carlo Search:\n";
         result += "Optimization Problem: ";
-        result += this.m_Problem.getStringRepresentationForProblem(this) + "\n";
+        result += this.optimizationProblem.getStringRepresentationForProblem(this) + "\n";
-        result += this.m_Population.getStringRepresentation();
+        result += this.population.getStringRepresentation();
         return result;
     }
 
@@ -218,26 +214,14 @@ public class MonteCarloSearch implements InterfaceOptimizer, java.io.Serializabl
      */
     @Override
     public void setIdentifier(String name) {
-        this.m_Identifier = name;
+        this.identifier = name;
     }
 
     @Override
     public String getIdentifier() {
-        return this.m_Identifier;
+        return this.identifier;
     }
 
-    /**
-     * ********************************************************************************************************************
-     * These are for GUI
-     */
-    /**
-     * This method returns a global info string
-     *
-     * @return description
-     */
-    public static String globalInfo() {
-        return "The Monte Carlo Search repeatively creates random individuals and stores the best individuals found.";
-    }
 
     /**
      * This method will return a naming String
@@ -258,12 +242,12 @@ public class MonteCarloSearch implements InterfaceOptimizer, java.io.Serializabl
      */
     @Override
     public Population getPopulation() {
-        return this.m_Population;
+        return this.population;
     }
 
     @Override
     public void setPopulation(Population pop) {
-        this.m_Population = pop;
+        this.population = pop;
     }
 
     public String populationTipText() {

src/eva2/optimization/tools/ParetoFrontLocalTester.java

@@ -16,6 +16,7 @@ import java.util.ArrayList;
  */
 public class ParetoFrontLocalTester {
 
+    // ToDo: Have this on another frame (won't show as JInternalFrame)
     private Plot m_Plot;
     private int index = 0;
     private BufferedWriter m_OutputFile = null;

src/eva2/tools/math/SpecialFunction.java

@@ -45,7 +45,7 @@ package eva2.tools.math;
  */
 
 
-public final class SpecialFunction extends Object {
+public final class SpecialFunction {
 
     /*
     ** machine constants