From ef36d0921889c3a804ae0890b9360b3b6f8243a2 Mon Sep 17 00:00:00 2001 From: Fabian Becker Date: Fri, 25 Jan 2013 13:20:25 +0000 Subject: [PATCH] Refactored "SetProblem" function to "setProblem". Coding Standards for the win. --- src/eva2/OptimizerFactory.java | 22 +++++++++---------- src/eva2/server/go/GOStandaloneVersion.java | 6 ++--- src/eva2/server/go/MOCCOStandalone.java | 2 +- .../server/go/mocco/MOCCOParameterizeGDF.java | 4 ++-- .../server/go/mocco/MOCCOParameterizeMO.java | 2 +- .../go/mocco/MOCCOParameterizeRefPoint.java | 4 ++-- .../server/go/mocco/MOCCOParameterizeSO.java | 2 +- .../go/mocco/MOCCOParameterizeSTEP.java | 4 ++-- .../mocco/MOCCOParameterizeTchebycheff.java | 4 ++-- src/eva2/server/go/mocco/MOCCOState.java | 4 ++-- .../migration/MOClusteringSeparation.java | 2 +- .../operators/migration/MOConeSeparation.java | 4 ++-- .../migration/MOXMeansSeparation.java | 2 +- .../go/operators/postprocess/PostProcess.java | 4 ++-- src/eva2/server/go/problems/F2Problem.java | 2 +- src/eva2/server/go/problems/F6Problem.java | 2 +- src/eva2/server/go/strategies/BOA.java | 2 +- .../go/strategies/BinaryScatterSearch.java | 2 +- src/eva2/server/go/strategies/CBNPSO.java | 4 ++-- .../CHCAdaptiveSearchAlgorithm.java | 2 +- .../go/strategies/ClusterBasedNichingEA.java | 4 ++-- .../go/strategies/ClusteringHillClimbing.java | 2 +- .../go/strategies/DifferentialEvolution.java | 2 +- .../DynamicParticleSwarmOptimization.java | 4 ++-- .../server/go/strategies/EsDpiNiching.java | 4 ++-- .../go/strategies/EvolutionStrategies.java | 2 +- .../strategies/EvolutionaryProgramming.java | 2 +- .../server/go/strategies/FloodAlgorithm.java | 2 +- .../go/strategies/GeneticAlgorithm.java | 2 +- .../strategies/GradientDescentAlgorithm.java | 4 ++-- .../server/go/strategies/HillClimbing.java | 2 +- .../go/strategies/InterfaceOptimizer.java | 2 +- .../server/go/strategies/IslandModelEA.java | 8 +++---- src/eva2/server/go/strategies/LTGA.java | 10 ++++----- src/eva2/server/go/strategies/MLTGA.java | 2 +- .../go/strategies/MemeticAlgorithm.java | 8 +++---- .../go/strategies/MonteCarloSearch.java | 2 +- .../go/strategies/MultiObjectiveCMAES.java | 2 +- .../go/strategies/MultiObjectiveEA.java | 6 ++--- .../go/strategies/NelderMeadSimplex.java | 4 ++-- src/eva2/server/go/strategies/NichePSO.java | 14 ++++++------ .../ParticleFilterOptimization.java | 2 +- .../ParticleSubSwarmOptimization.java | 4 ++-- .../strategies/ParticleSwarmOptimization.java | 2 +- .../PopulationBasedIncrementalLearning.java | 2 +- .../server/go/strategies/ScatterSearch.java | 4 ++-- .../go/strategies/SimulatedAnnealing.java | 2 +- .../server/go/strategies/SteadyStateGA.java | 2 +- .../go/strategies/ThresholdAlgorithm.java | 2 +- src/eva2/server/go/strategies/Tribes.java | 4 ++-- .../go/strategies/WingedMultiObjectiveEA.java | 14 ++++++------ .../server/modules/AbstractGOParameters.java | 10 ++++----- src/eva2/server/modules/Processor.java | 2 +- 53 files changed, 109 insertions(+), 109 deletions(-) diff --git a/src/eva2/OptimizerFactory.java b/src/eva2/OptimizerFactory.java index 4d5efcea..1825c207 100644 --- a/src/eva2/OptimizerFactory.java +++ b/src/eva2/OptimizerFactory.java @@ -127,7 +127,7 @@ public class OptimizerFactory { setTemplateOperators(problem, new NoMutation(), 0, new NoCrossover(), 0); DifferentialEvolution de = new DifferentialEvolution(); - de.SetProblem(problem); + de.setProblem(problem); de.getPopulation().setTargetSize(popsize); de.setDEType(DETypeEnum.DE2_CurrentToBest); de.setF(f); @@ -208,7 +208,7 @@ public class OptimizerFactory { // theES.setParentSelection(selection); // theES.setPartnerSelection(selection); theES.setEnvironmentSelection(selection); - theES.SetProblem(problem); + theES.setProblem(problem); theES.init(); if (listener != null) listener.registerPopulationStateChanged(theES.getPopulation(), ""); @@ -240,7 +240,7 @@ public class OptimizerFactory { setTemplateOperators(problem, mut, pm, cross, pc); GeneticAlgorithm ga = new GeneticAlgorithm(); - ga.SetProblem(problem); + ga.setProblem(problem); ga.getPopulation().setTargetSize(popsize); ga.setParentSelection(select); ga.setPartnerSelection(select); @@ -308,7 +308,7 @@ public class OptimizerFactory { InterfacePopulationChangedEventListener listener) { problem.initProblem(); - subOpt.SetProblem(problem); + subOpt.setProblem(problem); return new MultiObjectiveEA(subOpt, archiving, archiveSize, infoRetrieval, problem); @@ -376,7 +376,7 @@ public class OptimizerFactory { hc.setIdentifier("-"+popSize+"-"+mutator.getStringRepresentation()); hc.getPopulation().setTargetSize(popSize); hc.addPopulationChangedEventListener(listener); - hc.SetProblem(problem); + hc.setProblem(problem); hc.init(); if (listener != null) listener.registerPopulationStateChanged(hc.getPopulation(), ""); @@ -403,7 +403,7 @@ public class OptimizerFactory { MonteCarloSearch mc = new MonteCarloSearch(); mc.getPopulation().setTargetSize(popsize); mc.addPopulationChangedEventListener(listener); - mc.SetProblem(problem); + mc.setProblem(problem); mc.init(); if (listener != null) listener.registerPopulationStateChanged(mc.getPopulation(), ""); @@ -437,7 +437,7 @@ public class OptimizerFactory { setTemplateOperators(problem, new NoMutation(), 0, new NoCrossover(), 0); ParticleSwarmOptimization pso = new ParticleSwarmOptimization(); - pso.SetProblem(problem); + pso.setProblem(problem); pso.getPopulation().setTargetSize(popsize); pso.setPhi1(phi1); pso.setPhi2(phi2); @@ -480,7 +480,7 @@ public class OptimizerFactory { SimulatedAnnealing sa = new SimulatedAnnealing(); sa.setAlpha(alpha); sa.setInitialTemperature(temperature); - sa.SetProblem(problem); + sa.setProblem(problem); sa.getPopulation().setTargetSize(popsize); sa.addPopulationChangedEventListener(listener); sa.init(); @@ -518,7 +518,7 @@ public class OptimizerFactory { pbil.setPositiveSamples(positiveSamples); pbil.addPopulationChangedEventListener(listener); - pbil.SetProblem(problem); + pbil.setProblem(problem); if (listener != null) listener.registerPopulationStateChanged(pbil.getPopulation(), ""); @@ -763,7 +763,7 @@ public class OptimizerFactory { InterfaceTerminator term) { GOParameters params = new GOParameters(); params.setProblem(problem); - opt.SetProblem(problem); + opt.setProblem(problem); opt.setPopulation(pop); params.setOptimizer(opt); params.setTerminator(term); @@ -1340,7 +1340,7 @@ public class OptimizerFactory { AbstractOptimizationProblem problem, int evalCycle, int popSize, double minImprovement, PostProcessMethod method, double hcInitialStep, double hcStepThresh, double sigmaClust) { ClusteringHillClimbing chc = new ClusteringHillClimbing(); - chc.SetProblem(problem); + chc.setProblem(problem); chc.setEvalCycle(evalCycle); chc.setInitialPopSize(popSize); diff --git a/src/eva2/server/go/GOStandaloneVersion.java b/src/eva2/server/go/GOStandaloneVersion.java index 4a0a6792..3f45f414 100644 --- a/src/eva2/server/go/GOStandaloneVersion.java +++ b/src/eva2/server/go/GOStandaloneVersion.java @@ -312,7 +312,7 @@ public class GOStandaloneVersion implements InterfaceGOStandalone, InterfacePopu ((GAIndividualDoubleData)tmpIndy).setMutationProbability(1.0); ((F1Problem)problem).setEAIndividual(tmpIndy); //((FGRNInferringProblem)this.m_Problem).setStructreSkelInterval(1); - this.m_GO.getOptimizer().SetProblem(problem); + this.m_GO.getOptimizer().setProblem(problem); this.m_GO.getOptimizer().addPopulationChangedEventListener(this); this.doWork(); break; @@ -329,7 +329,7 @@ public class GOStandaloneVersion implements InterfaceGOStandalone, InterfacePopu ((F1Problem)problem).setEAIndividual(tmpIndy); //((FGRNInferringProblem)this.m_Problem).setUseHEigenMatrix(true); //((FGRNInferringProblem)this.m_Problem).setUseOnlyPositiveNumbers(true); - this.m_GO.getOptimizer().SetProblem(problem); + this.m_GO.getOptimizer().setProblem(problem); this.m_GO.getOptimizer().addPopulationChangedEventListener(this); this.doWork(); break; @@ -375,7 +375,7 @@ public class GOStandaloneVersion implements InterfaceGOStandalone, InterfacePopu // init problem this.m_GO.getProblem().initProblem(); - this.m_GO.getOptimizer().SetProblem(this.m_GO.getProblem()); + this.m_GO.getOptimizer().setProblem(this.m_GO.getProblem()); // int optimizer and population //this.m_GO.getOptimizer().init(); diff --git a/src/eva2/server/go/MOCCOStandalone.java b/src/eva2/server/go/MOCCOStandalone.java index fe715b48..eef7d792 100644 --- a/src/eva2/server/go/MOCCOStandalone.java +++ b/src/eva2/server/go/MOCCOStandalone.java @@ -363,7 +363,7 @@ public class MOCCOStandalone implements InterfaceGOStandalone, InterfacePopulati if (this.m_JFrame != null) { } this.m_StillWorking = true; - this.m_State.m_Optimizer.SetProblem(this.m_State.m_CurrentProblem); + this.m_State.m_Optimizer.setProblem(this.m_State.m_CurrentProblem); if (this.m_Debug) System.out.println(""+this.m_State.m_Optimizer.getStringRepresentation()); this.m_State.m_CurrentProblem.evaluate(this.m_State.m_Optimizer.getPopulation()); this.m_State.m_Optimizer.getPopulation().SetFunctionCalls(0); diff --git a/src/eva2/server/go/mocco/MOCCOParameterizeGDF.java b/src/eva2/server/go/mocco/MOCCOParameterizeGDF.java index 9a436947..268056b3 100644 --- a/src/eva2/server/go/mocco/MOCCOParameterizeGDF.java +++ b/src/eva2/server/go/mocco/MOCCOParameterizeGDF.java @@ -125,7 +125,7 @@ public class MOCCOParameterizeGDF extends MOCCOPhase implements InterfaceProcess gbc.gridwidth = 1; this.m_EOpt = new GeneralGOEProperty(); this.m_Opt = new GeneticAlgorithm(); - this.m_Opt.SetProblem(this.m_Mocco.m_State.m_CurrentProblem); + this.m_Opt.setProblem(this.m_Mocco.m_State.m_CurrentProblem); this.m_Mocco.m_State.m_Optimizer = this.m_Opt; this.m_EOpt.m_Name = "Island Model EA"; try { @@ -217,7 +217,7 @@ public class MOCCOParameterizeGDF extends MOCCOPhase implements InterfaceProcess PropertyDoubleArray da = new PropertyDoubleArray(w); wf.setOutputDimension(da.getNumRows()); wf.setWeights(da); - m_Opt.SetProblem(m_Mocco.m_State.m_CurrentProblem); + m_Opt.setProblem(m_Mocco.m_State.m_CurrentProblem); m_Mocco.m_State.m_Optimizer = m_Opt; m_Mocco.m_JPanelControl.removeAll(); m_Mocco.m_JPanelControl.validate(); diff --git a/src/eva2/server/go/mocco/MOCCOParameterizeMO.java b/src/eva2/server/go/mocco/MOCCOParameterizeMO.java index f8784715..79cee67d 100644 --- a/src/eva2/server/go/mocco/MOCCOParameterizeMO.java +++ b/src/eva2/server/go/mocco/MOCCOParameterizeMO.java @@ -138,7 +138,7 @@ public class MOCCOParameterizeMO extends MOCCOPhase implements InterfaceProcessE //m_Mocco.m_State.m_Optimizer = (InterfaceOptimizer)m_Optimizer.clone(); m_Mocco.m_JPanelControl.removeAll(); m_Mocco.m_JPanelParameters.removeAll(); - m_Mocco.m_State.m_Optimizer.SetProblem(m_Mocco.m_State.m_CurrentProblem); + m_Mocco.m_State.m_Optimizer.setProblem(m_Mocco.m_State.m_CurrentProblem); Population pop = m_Mocco.m_State.m_Optimizer.getPopulation(); pop.clear(); if (pop.getArchive() != null) pop.getArchive().clear(); diff --git a/src/eva2/server/go/mocco/MOCCOParameterizeRefPoint.java b/src/eva2/server/go/mocco/MOCCOParameterizeRefPoint.java index 169e0e4c..f575a0ce 100644 --- a/src/eva2/server/go/mocco/MOCCOParameterizeRefPoint.java +++ b/src/eva2/server/go/mocco/MOCCOParameterizeRefPoint.java @@ -137,7 +137,7 @@ public class MOCCOParameterizeRefPoint extends MOCCOPhase implements InterfacePr this.m_Island.setMigrationRate(2); this.m_Island.setMigrationStrategy(new SOBestMigration()); this.m_Island.setNumberLocalCPUs(this.m_Perturbations); - this.m_Island.SetProblem(this.m_Mocco.m_State.m_CurrentProblem); + this.m_Island.setProblem(this.m_Mocco.m_State.m_CurrentProblem); this.m_Mocco.m_State.m_Optimizer = this.m_Island; this.m_EIMEA.m_Name = "Island Model EA"; try { @@ -234,7 +234,7 @@ public class MOCCOParameterizeRefPoint extends MOCCOPhase implements InterfacePr // m_Island.setNumberLocalCPUs(m_Perturbations); // } m_Mocco.m_State.m_Optimizer = m_Island; - m_Mocco.m_State.m_Optimizer.SetProblem(m_Mocco.m_State.m_CurrentProblem); + m_Mocco.m_State.m_Optimizer.setProblem(m_Mocco.m_State.m_CurrentProblem); m_Island.init(); double[] tmpD; MOSOLpMetric[] tmpLPs = new MOSOLpMetric[m_Perturbations]; diff --git a/src/eva2/server/go/mocco/MOCCOParameterizeSO.java b/src/eva2/server/go/mocco/MOCCOParameterizeSO.java index bd310001..c744d1ee 100644 --- a/src/eva2/server/go/mocco/MOCCOParameterizeSO.java +++ b/src/eva2/server/go/mocco/MOCCOParameterizeSO.java @@ -66,7 +66,7 @@ public class MOCCOParameterizeSO extends MOCCOPhase implements InterfaceProcessE "a Genetic Algorithms, please parameterize accordingly.", "Warning", JOptionPane.WARNING_MESSAGE); this.m_Mocco.m_State.m_Optimizer = new GeneticAlgorithm(); - this.m_Mocco.m_State.m_Optimizer.SetProblem(this.m_Mocco.m_State.m_CurrentProblem); + this.m_Mocco.m_State.m_Optimizer.setProblem(this.m_Mocco.m_State.m_CurrentProblem); } this.m_Mocco.m_JPanelParameters.removeAll(); this.m_Mocco.m_JPanelParameters.setLayout(new BorderLayout()); diff --git a/src/eva2/server/go/mocco/MOCCOParameterizeSTEP.java b/src/eva2/server/go/mocco/MOCCOParameterizeSTEP.java index 14d6cdbc..e45133d5 100644 --- a/src/eva2/server/go/mocco/MOCCOParameterizeSTEP.java +++ b/src/eva2/server/go/mocco/MOCCOParameterizeSTEP.java @@ -167,7 +167,7 @@ public class MOCCOParameterizeSTEP extends MOCCOPhase implements InterfaceProces gbc.gridwidth = 1; this.m_EOpt = new GeneralGOEProperty(); this.m_Opt = new GeneticAlgorithm(); - this.m_Opt.SetProblem(this.m_Mocco.m_State.m_CurrentProblem); + this.m_Opt.setProblem(this.m_Mocco.m_State.m_CurrentProblem); this.m_Mocco.m_State.m_Optimizer = this.m_Opt; this.m_EOpt.m_Name = "Island Model EA"; try { @@ -294,7 +294,7 @@ public class MOCCOParameterizeSTEP extends MOCCOPhase implements InterfaceProces double[] setWeights = mapObjectives2Fitness(weights); PropertyDoubleArray da = new PropertyDoubleArray(setWeights); wf.setWeights(da); - m_Opt.SetProblem(m_Mocco.m_State.m_CurrentProblem); + m_Opt.setProblem(m_Mocco.m_State.m_CurrentProblem); m_Mocco.m_State.m_Optimizer = m_Opt; m_Mocco.m_JPanelControl.removeAll(); m_Mocco.m_JPanelControl.validate(); diff --git a/src/eva2/server/go/mocco/MOCCOParameterizeTchebycheff.java b/src/eva2/server/go/mocco/MOCCOParameterizeTchebycheff.java index 6e0ec110..6a746f80 100644 --- a/src/eva2/server/go/mocco/MOCCOParameterizeTchebycheff.java +++ b/src/eva2/server/go/mocco/MOCCOParameterizeTchebycheff.java @@ -114,7 +114,7 @@ public class MOCCOParameterizeTchebycheff extends MOCCOPhase implements Interfac this.m_Island.setMigrationRate(2); this.m_Island.setMigrationStrategy(new SOBestMigration()); this.m_Island.setNumberLocalCPUs(this.m_Perturbations); - this.m_Island.SetProblem(this.m_Mocco.m_State.m_CurrentProblem); + this.m_Island.setProblem(this.m_Mocco.m_State.m_CurrentProblem); this.m_Mocco.m_State.m_Optimizer = this.m_Island; this.m_EIMEA.m_Name = "Island Model EA"; try { @@ -241,7 +241,7 @@ public class MOCCOParameterizeTchebycheff extends MOCCOPhase implements Interfac // m_Island.setNumberLocalCPUs(m_Perturbations); // } m_Mocco.m_State.m_Optimizer = m_Island; - m_Mocco.m_State.m_Optimizer.SetProblem(m_Mocco.m_State.m_CurrentProblem); + m_Mocco.m_State.m_Optimizer.setProblem(m_Mocco.m_State.m_CurrentProblem); m_Island.init(); double[] tmpD; double sum = 0, l = 0, u = 1; diff --git a/src/eva2/server/go/mocco/MOCCOState.java b/src/eva2/server/go/mocco/MOCCOState.java index 0a5c6020..54d891ef 100644 --- a/src/eva2/server/go/mocco/MOCCOState.java +++ b/src/eva2/server/go/mocco/MOCCOState.java @@ -56,14 +56,14 @@ public class MOCCOState { this.m_BackupOptimizer = null; } this.m_Optimizer.setPopulation(pop); - this.m_Optimizer.SetProblem(this.m_CurrentProblem); + this.m_Optimizer.setProblem(this.m_CurrentProblem); this.m_CurrentProblem.evaluate(this.m_Optimizer.getPopulation()); } public void makeBackup() { this.m_BackupProblem = (InterfaceOptimizationProblem)this.m_CurrentProblem.clone(); this.m_BackupOptimizer = (InterfaceOptimizer)this.m_Optimizer.clone(); - this.m_BackupOptimizer.SetProblem(null); + this.m_BackupOptimizer.setProblem(null); } public void addPopulation2History(Population pop) { diff --git a/src/eva2/server/go/operators/migration/MOClusteringSeparation.java b/src/eva2/server/go/operators/migration/MOClusteringSeparation.java index 11228458..6ed687b5 100644 --- a/src/eva2/server/go/operators/migration/MOClusteringSeparation.java +++ b/src/eva2/server/go/operators/migration/MOClusteringSeparation.java @@ -201,7 +201,7 @@ public class MOClusteringSeparation implements InterfaceMigration, java.io.Seria // else out += "\n Using objective space."; // System.out.println(""+out); // } - islands[i].SetProblem(prob); + islands[i].setProblem(prob); } } } diff --git a/src/eva2/server/go/operators/migration/MOConeSeparation.java b/src/eva2/server/go/operators/migration/MOConeSeparation.java index 6175c182..37b9bbc4 100644 --- a/src/eva2/server/go/operators/migration/MOConeSeparation.java +++ b/src/eva2/server/go/operators/migration/MOConeSeparation.java @@ -266,7 +266,7 @@ public class MOConeSeparation implements InterfaceMigration, java.io.Serializabl ((AbstractMultiObjectiveOptimizationProblem)prob).m_AreaConst4Parallelization.add(b); } - islands[i].SetProblem(prob); + islands[i].setProblem(prob); } } } @@ -360,7 +360,7 @@ public class MOConeSeparation implements InterfaceMigration, java.io.Serializabl ((AbstractMultiObjectiveOptimizationProblem)prob).m_AreaConst4Parallelization.add(sts); ((AbstractMultiObjectiveOptimizationProblem)prob).m_AreaConst4Parallelization.add(bts); } - islands[i].SetProblem(prob); + islands[i].setProblem(prob); // if (true) { // prob.evaluate(newIPOP[i]); // System.out.println("Invalid Individual in Island "+i+" ("+newIPOP[i].size()+"): "); diff --git a/src/eva2/server/go/operators/migration/MOXMeansSeparation.java b/src/eva2/server/go/operators/migration/MOXMeansSeparation.java index c89755ce..4217c62a 100644 --- a/src/eva2/server/go/operators/migration/MOXMeansSeparation.java +++ b/src/eva2/server/go/operators/migration/MOXMeansSeparation.java @@ -207,7 +207,7 @@ public class MOXMeansSeparation implements InterfaceMigration, java.io.Serializa // else out += "\n Using objective space."; // System.out.println(""+out); // } - islands[i].SetProblem(prob); + islands[i].setProblem(prob); } } } diff --git a/src/eva2/server/go/operators/postprocess/PostProcess.java b/src/eva2/server/go/operators/postprocess/PostProcess.java index a11a5529..fa5ae9d1 100644 --- a/src/eva2/server/go/operators/postprocess/PostProcess.java +++ b/src/eva2/server/go/operators/postprocess/PostProcess.java @@ -386,7 +386,7 @@ public class PostProcess { public static void processWithHC(Population pop, AbstractOptimizationProblem problem, InterfaceTerminator term, InterfaceMutation mute) { HillClimbing hc = new HillClimbing(); // HC depends heavily on the selected mutation operator! - hc.SetProblem(problem); + hc.setProblem(problem); mute.init(problem.getIndividualTemplate(), problem); hc.SetMutationOperator(mute); if (pop.size() != pop.getTargetSize()) { @@ -405,7 +405,7 @@ public class PostProcess { public static int processWithGDA(Population pop, AbstractOptimizationProblem problem, InterfaceTerminator term, int baseEvals, double minStepSize, double maxStepSize) { GradientDescentAlgorithm gda = new GradientDescentAlgorithm(); gda.setAdaptStepSizeLocally(true); - gda.SetProblem(problem); + gda.setProblem(problem); gda.setLocalMinStepSize(minStepSize); gda.setLocalMaxStepSize(maxStepSize); gda.setRecovery(false); diff --git a/src/eva2/server/go/problems/F2Problem.java b/src/eva2/server/go/problems/F2Problem.java index e7e545d1..2d8b49fb 100644 --- a/src/eva2/server/go/problems/F2Problem.java +++ b/src/eva2/server/go/problems/F2Problem.java @@ -111,7 +111,7 @@ public class F2Problem extends AbstractProblemDoubleOffset implements InterfaceL private void initLS() { localSearchOptimizer = new GradientDescentAlgorithm(); - localSearchOptimizer.SetProblem(this); + localSearchOptimizer.setProblem(this); localSearchOptimizer.init(); } diff --git a/src/eva2/server/go/problems/F6Problem.java b/src/eva2/server/go/problems/F6Problem.java index bc9cdb08..24303cbf 100644 --- a/src/eva2/server/go/problems/F6Problem.java +++ b/src/eva2/server/go/problems/F6Problem.java @@ -142,7 +142,7 @@ implements InterfaceMultimodalProblem, InterfaceFirstOrderDerivableProblem, Inte private void initLS() { localSearchOptimizer = new GradientDescentAlgorithm(); - localSearchOptimizer.SetProblem(this); + localSearchOptimizer.setProblem(this); localSearchOptimizer.init(); } diff --git a/src/eva2/server/go/strategies/BOA.java b/src/eva2/server/go/strategies/BOA.java index 586dc081..16f5cabc 100644 --- a/src/eva2/server/go/strategies/BOA.java +++ b/src/eva2/server/go/strategies/BOA.java @@ -599,7 +599,7 @@ public class BOA implements InterfaceOptimizer, java.io.Serializable { return this.m_Identifier; } - public void SetProblem(InterfaceOptimizationProblem problem) { + public void setProblem(InterfaceOptimizationProblem problem) { this.problem = (AbstractOptimizationProblem) problem; } diff --git a/src/eva2/server/go/strategies/BinaryScatterSearch.java b/src/eva2/server/go/strategies/BinaryScatterSearch.java index 85555a89..09ddbbb9 100644 --- a/src/eva2/server/go/strategies/BinaryScatterSearch.java +++ b/src/eva2/server/go/strategies/BinaryScatterSearch.java @@ -731,7 +731,7 @@ public class BinaryScatterSearch implements InterfaceOptimizer, java.io.Serializ return this.m_Identifier; } - public void SetProblem(InterfaceOptimizationProblem problem) { + public void setProblem(InterfaceOptimizationProblem problem) { this.problem = (AbstractOptimizationProblem) problem; } diff --git a/src/eva2/server/go/strategies/CBNPSO.java b/src/eva2/server/go/strategies/CBNPSO.java index c4790715..18cd0d53 100644 --- a/src/eva2/server/go/strategies/CBNPSO.java +++ b/src/eva2/server/go/strategies/CBNPSO.java @@ -67,8 +67,8 @@ public class CBNPSO extends ClusterBasedNichingEA implements Serializable { } @Override - public void SetProblem(InterfaceOptimizationProblem problem) { - super.SetProblem(problem); + public void setProblem(InterfaceOptimizationProblem problem) { + super.setProblem(problem); if (problem instanceof AbstractProblemDouble) { AbstractProblemDouble dblProb = ((AbstractProblemDouble)problem); adaptMinMaxSwarmSizeByDim(dblProb); diff --git a/src/eva2/server/go/strategies/CHCAdaptiveSearchAlgorithm.java b/src/eva2/server/go/strategies/CHCAdaptiveSearchAlgorithm.java index 69824742..3194674b 100644 --- a/src/eva2/server/go/strategies/CHCAdaptiveSearchAlgorithm.java +++ b/src/eva2/server/go/strategies/CHCAdaptiveSearchAlgorithm.java @@ -238,7 +238,7 @@ public class CHCAdaptiveSearchAlgorithm implements InterfaceOptimizer, java.io.S /** This method will set the problem that is to be optimized * @param problem */ - public void SetProblem (InterfaceOptimizationProblem problem) { + public void setProblem (InterfaceOptimizationProblem problem) { this.m_Problem = problem; } public InterfaceOptimizationProblem getProblem () { diff --git a/src/eva2/server/go/strategies/ClusterBasedNichingEA.java b/src/eva2/server/go/strategies/ClusterBasedNichingEA.java index 7c4babe2..8a2b38b4 100644 --- a/src/eva2/server/go/strategies/ClusterBasedNichingEA.java +++ b/src/eva2/server/go/strategies/ClusterBasedNichingEA.java @@ -972,9 +972,9 @@ public class ClusterBasedNichingEA implements InterfacePopulationChangedEventLis /** This method will set the problem that is to be optimized * @param problem */ - public void SetProblem (InterfaceOptimizationProblem problem) { + public void setProblem (InterfaceOptimizationProblem problem) { this.m_Problem = problem; - this.m_Optimizer.SetProblem(this.m_Problem); + this.m_Optimizer.setProblem(this.m_Problem); } public InterfaceOptimizationProblem getProblem () { return this.m_Problem; diff --git a/src/eva2/server/go/strategies/ClusteringHillClimbing.java b/src/eva2/server/go/strategies/ClusteringHillClimbing.java index d465d0e5..7fc4364f 100644 --- a/src/eva2/server/go/strategies/ClusteringHillClimbing.java +++ b/src/eva2/server/go/strategies/ClusteringHillClimbing.java @@ -107,7 +107,7 @@ InterfaceOptimizer, Serializable, InterfaceAdditionalPopulationInformer { /** This method will set the problem that is to be optimized * @param problem */ - public void SetProblem (InterfaceOptimizationProblem problem) { + public void setProblem (InterfaceOptimizationProblem problem) { this.m_Problem = problem; } public InterfaceOptimizationProblem getProblem () { diff --git a/src/eva2/server/go/strategies/DifferentialEvolution.java b/src/eva2/server/go/strategies/DifferentialEvolution.java index 971fafeb..2d871908 100644 --- a/src/eva2/server/go/strategies/DifferentialEvolution.java +++ b/src/eva2/server/go/strategies/DifferentialEvolution.java @@ -665,7 +665,7 @@ public class DifferentialEvolution implements InterfaceOptimizer, java.io.Serial /** This method will set the problem that is to be optimized * @param problem */ - public void SetProblem (InterfaceOptimizationProblem problem) { + public void setProblem (InterfaceOptimizationProblem problem) { this.m_Problem = (AbstractOptimizationProblem)problem; } public InterfaceOptimizationProblem getProblem () { diff --git a/src/eva2/server/go/strategies/DynamicParticleSwarmOptimization.java b/src/eva2/server/go/strategies/DynamicParticleSwarmOptimization.java index eb973b16..99aac038 100644 --- a/src/eva2/server/go/strategies/DynamicParticleSwarmOptimization.java +++ b/src/eva2/server/go/strategies/DynamicParticleSwarmOptimization.java @@ -487,8 +487,8 @@ public class DynamicParticleSwarmOptimization extends ParticleSwarmOptimization } - public void SetProblem (InterfaceOptimizationProblem problem) { - super.SetProblem(problem); + public void setProblem (InterfaceOptimizationProblem problem) { + super.setProblem(problem); if (problem instanceof AbstractOptimizationProblem) { ((AbstractOptimizationProblem)problem).informAboutOptimizer(this); } diff --git a/src/eva2/server/go/strategies/EsDpiNiching.java b/src/eva2/server/go/strategies/EsDpiNiching.java index 4bbd94ac..9e6cde28 100644 --- a/src/eva2/server/go/strategies/EsDpiNiching.java +++ b/src/eva2/server/go/strategies/EsDpiNiching.java @@ -243,7 +243,7 @@ public class EsDpiNiching implements InterfaceOptimizer, Serializable, Interface // Trying to come close to the selection scheme of Shir&Bäck'05: peakOpts[i].setParentSelection(parentSel); peakOpts[i].setPartnerSelection(new SelectBestSingle(true)); - peakOpts[i].SetProblem(problem); + peakOpts[i].setProblem(problem); peakOpts[i].init(); peakOpts[i].setLambda(lambdaPerPeak); // set lambda after initialization peakOpts[i].setForceOrigPopSize(false); @@ -1079,7 +1079,7 @@ public class EsDpiNiching implements InterfaceOptimizer, Serializable, Interface return problem; } - public void SetProblem(InterfaceOptimizationProblem prob) { + public void setProblem(InterfaceOptimizationProblem prob) { this.problem = prob; } diff --git a/src/eva2/server/go/strategies/EvolutionStrategies.java b/src/eva2/server/go/strategies/EvolutionStrategies.java index a946ef5a..a6ba1040 100644 --- a/src/eva2/server/go/strategies/EvolutionStrategies.java +++ b/src/eva2/server/go/strategies/EvolutionStrategies.java @@ -268,7 +268,7 @@ public class EvolutionStrategies implements InterfaceOptimizer, java.io.Serializ * * @param problem */ - public void SetProblem(InterfaceOptimizationProblem problem) { + public void setProblem(InterfaceOptimizationProblem problem) { this.optimizationProblem = problem; } diff --git a/src/eva2/server/go/strategies/EvolutionaryProgramming.java b/src/eva2/server/go/strategies/EvolutionaryProgramming.java index a484a689..050d6058 100644 --- a/src/eva2/server/go/strategies/EvolutionaryProgramming.java +++ b/src/eva2/server/go/strategies/EvolutionaryProgramming.java @@ -131,7 +131,7 @@ public class EvolutionaryProgramming implements InterfaceOptimizer, java.io.Seri /** This method will set the problem that is to be optimized * @param problem */ - public void SetProblem (InterfaceOptimizationProblem problem) { + public void setProblem (InterfaceOptimizationProblem problem) { this.m_Problem = problem; } public InterfaceOptimizationProblem getProblem () { diff --git a/src/eva2/server/go/strategies/FloodAlgorithm.java b/src/eva2/server/go/strategies/FloodAlgorithm.java index ec0d558f..a13c9032 100644 --- a/src/eva2/server/go/strategies/FloodAlgorithm.java +++ b/src/eva2/server/go/strategies/FloodAlgorithm.java @@ -120,7 +120,7 @@ public class FloodAlgorithm implements InterfaceOptimizer, java.io.Serializable /** This method will set the problem that is to be optimized * @param problem */ - public void SetProblem (InterfaceOptimizationProblem problem) { + public void setProblem (InterfaceOptimizationProblem problem) { this.m_Problem = problem; } public InterfaceOptimizationProblem getProblem () { diff --git a/src/eva2/server/go/strategies/GeneticAlgorithm.java b/src/eva2/server/go/strategies/GeneticAlgorithm.java index 86ecf86f..6eb48743 100644 --- a/src/eva2/server/go/strategies/GeneticAlgorithm.java +++ b/src/eva2/server/go/strategies/GeneticAlgorithm.java @@ -197,7 +197,7 @@ public class GeneticAlgorithm implements InterfaceOptimizer, java.io.Serializabl /** This method will set the problem that is to be optimized * @param problem */ - public void SetProblem (InterfaceOptimizationProblem problem) { + public void setProblem (InterfaceOptimizationProblem problem) { this.m_Problem = problem; } public InterfaceOptimizationProblem getProblem () { diff --git a/src/eva2/server/go/strategies/GradientDescentAlgorithm.java b/src/eva2/server/go/strategies/GradientDescentAlgorithm.java index f1689fcb..339c8070 100644 --- a/src/eva2/server/go/strategies/GradientDescentAlgorithm.java +++ b/src/eva2/server/go/strategies/GradientDescentAlgorithm.java @@ -324,7 +324,7 @@ public class GradientDescentAlgorithm implements InterfaceOptimizer, java.io.Ser return this.m_Identifier; } - public void SetProblem(InterfaceOptimizationProblem problem) { + public void setProblem(InterfaceOptimizationProblem problem) { m_Problem = problem; } @@ -350,7 +350,7 @@ public class GradientDescentAlgorithm implements InterfaceOptimizer, java.io.Ser public static void main(String[] args) { GradientDescentAlgorithm program = new GradientDescentAlgorithm(); InterfaceOptimizationProblem problem = new F1Problem(); - program.SetProblem(problem); + program.setProblem(problem); program.init(); for (int i = 0; i < 100; i++) { program.optimize(); diff --git a/src/eva2/server/go/strategies/HillClimbing.java b/src/eva2/server/go/strategies/HillClimbing.java index 65866502..8849fb26 100644 --- a/src/eva2/server/go/strategies/HillClimbing.java +++ b/src/eva2/server/go/strategies/HillClimbing.java @@ -128,7 +128,7 @@ public class HillClimbing implements InterfaceOptimizer, java.io.Serializable { /** This method will set the problem that is to be optimized * @param problem */ - public void SetProblem (InterfaceOptimizationProblem problem) { + public void setProblem (InterfaceOptimizationProblem problem) { this.m_Problem = problem; } public InterfaceOptimizationProblem getProblem () { diff --git a/src/eva2/server/go/strategies/InterfaceOptimizer.java b/src/eva2/server/go/strategies/InterfaceOptimizer.java index 74b76f73..5265f5a2 100644 --- a/src/eva2/server/go/strategies/InterfaceOptimizer.java +++ b/src/eva2/server/go/strategies/InterfaceOptimizer.java @@ -94,7 +94,7 @@ public interface InterfaceOptimizer { * * @param problem */ - public void SetProblem (InterfaceOptimizationProblem problem); + public void setProblem (InterfaceOptimizationProblem problem); public InterfaceOptimizationProblem getProblem (); /** This method will return a string describing all properties of the optimizer diff --git a/src/eva2/server/go/strategies/IslandModelEA.java b/src/eva2/server/go/strategies/IslandModelEA.java index 58ea0c2a..2cf7cffe 100644 --- a/src/eva2/server/go/strategies/IslandModelEA.java +++ b/src/eva2/server/go/strategies/IslandModelEA.java @@ -101,7 +101,7 @@ public class IslandModelEA implements InterfacePopulationChangedEventListener, I this.m_Population.clear(); this.m_Population.init(); this.m_Optimizer.init(); - this.m_Optimizer.SetProblem(this.m_Problem); + this.m_Optimizer.setProblem(this.m_Problem); this.m_Optimizer.setPopulation((Population)m_Population.clone()); InterfacePopulationChangedEventListener myLocal = null; if (this.m_localOnly) { @@ -171,7 +171,7 @@ public class IslandModelEA implements InterfacePopulationChangedEventListener, I this.m_Population.incrGeneration(); } this.m_Optimizer.init(); - this.m_Optimizer.SetProblem(this.m_Problem); + this.m_Optimizer.setProblem(this.m_Problem); InterfacePopulationChangedEventListener myLocal = null; if (this.m_localOnly) { // this is running on the local machine @@ -297,9 +297,9 @@ public class IslandModelEA implements InterfacePopulationChangedEventListener, I /** This method will set the problem that is to be optimized * @param problem */ - public void SetProblem (InterfaceOptimizationProblem problem) { + public void setProblem (InterfaceOptimizationProblem problem) { this.m_Problem = problem; - this.m_Optimizer.SetProblem(problem); + this.m_Optimizer.setProblem(problem); } public InterfaceOptimizationProblem getProblem () { return this.m_Problem; diff --git a/src/eva2/server/go/strategies/LTGA.java b/src/eva2/server/go/strategies/LTGA.java index b6915439..b4559dda 100644 --- a/src/eva2/server/go/strategies/LTGA.java +++ b/src/eva2/server/go/strategies/LTGA.java @@ -118,7 +118,7 @@ public class LTGA implements InterfaceOptimizer, java.io.Serializable, Interface @Override public void init() { - defaultInit(); + this.defaultInit(); this.problem.initPopulation(this.population); this.evaluatePopulation(this.population); this.firePropertyChangedEvent(Population.nextGenerationPerformed); @@ -150,7 +150,7 @@ public class LTGA implements InterfaceOptimizer, java.io.Serializable, Interface @Override public void initByPopulation(Population pop, boolean reset) { if (reset) { - init(); + this.init(); } else { defaultInit(); this.population = pop; @@ -247,7 +247,7 @@ public class LTGA implements InterfaceOptimizer, java.io.Serializable, Interface @Override public void optimize() { this.problem.evaluatePopulationStart(this.population); - Stack> linkageTree = buildLinkageTree(); + Stack> linkageTree = this.buildLinkageTree(); Population newPop = new Population(this.popSize); if(elitism){ Population firstIndies = this.population.getBestNIndividuals(2, fitCrit); @@ -259,7 +259,7 @@ public class LTGA implements InterfaceOptimizer, java.io.Serializable, Interface continue; } Population indies = this.population.getRandNIndividuals(2); - Population newIndies = buildNewIndies(indies, linkageTree); + Population newIndies = this.buildNewIndies(indies, linkageTree); newPop.addAll(newIndies); } this.population.clear(); @@ -341,7 +341,7 @@ public class LTGA implements InterfaceOptimizer, java.io.Serializable, Interface } @Override - public void SetProblem(InterfaceOptimizationProblem problem) { + public void setProblem(InterfaceOptimizationProblem problem) { this.problem = (AbstractOptimizationProblem) problem; } diff --git a/src/eva2/server/go/strategies/MLTGA.java b/src/eva2/server/go/strategies/MLTGA.java index 64bd397f..122c995c 100644 --- a/src/eva2/server/go/strategies/MLTGA.java +++ b/src/eva2/server/go/strategies/MLTGA.java @@ -320,7 +320,7 @@ public class MLTGA implements InterfaceOptimizer, java.io.Serializable, Interfac } @Override - public void SetProblem(InterfaceOptimizationProblem problem) { + public void setProblem(InterfaceOptimizationProblem problem) { this.problem = (AbstractOptimizationProblem) problem; } diff --git a/src/eva2/server/go/strategies/MemeticAlgorithm.java b/src/eva2/server/go/strategies/MemeticAlgorithm.java index 85d5f6e3..54cbaeea 100644 --- a/src/eva2/server/go/strategies/MemeticAlgorithm.java +++ b/src/eva2/server/go/strategies/MemeticAlgorithm.java @@ -98,7 +98,7 @@ public class MemeticAlgorithm implements InterfaceOptimizer, public void init() { // counter = 0; - this.m_GlobalOptimizer.SetProblem(this.m_Problem); + this.m_GlobalOptimizer.setProblem(this.m_Problem); this.m_GlobalOptimizer.init(); this.evaluatePopulation(this.m_GlobalOptimizer.getPopulation()); this.firePropertyChangedEvent(Population.nextGenerationPerformed); @@ -225,9 +225,9 @@ public class MemeticAlgorithm implements InterfaceOptimizer, * * @param problem */ - public void SetProblem(InterfaceOptimizationProblem problem) { + public void setProblem(InterfaceOptimizationProblem problem) { this.m_Problem = problem; - this.m_GlobalOptimizer.SetProblem(this.m_Problem); + this.m_GlobalOptimizer.setProblem(this.m_Problem); } public InterfaceOptimizationProblem getProblem() { @@ -320,7 +320,7 @@ public class MemeticAlgorithm implements InterfaceOptimizer, */ public void setGlobalOptimizer(InterfaceOptimizer m_GlobalOptimizer) { this.m_GlobalOptimizer = m_GlobalOptimizer; - this.m_GlobalOptimizer.SetProblem(this.getProblem()); + this.m_GlobalOptimizer.setProblem(this.getProblem()); this.init(); } diff --git a/src/eva2/server/go/strategies/MonteCarloSearch.java b/src/eva2/server/go/strategies/MonteCarloSearch.java index 2e2031e1..49559184 100644 --- a/src/eva2/server/go/strategies/MonteCarloSearch.java +++ b/src/eva2/server/go/strategies/MonteCarloSearch.java @@ -103,7 +103,7 @@ public class MonteCarloSearch implements InterfaceOptimizer, java.io.Serializabl /** This method will set the problem that is to be optimized * @param problem */ - public void SetProblem (InterfaceOptimizationProblem problem) { + public void setProblem (InterfaceOptimizationProblem problem) { this.m_Problem = problem; } public InterfaceOptimizationProblem getProblem () { diff --git a/src/eva2/server/go/strategies/MultiObjectiveCMAES.java b/src/eva2/server/go/strategies/MultiObjectiveCMAES.java index 0a0ce07b..e93b58d0 100644 --- a/src/eva2/server/go/strategies/MultiObjectiveCMAES.java +++ b/src/eva2/server/go/strategies/MultiObjectiveCMAES.java @@ -88,7 +88,7 @@ public class MultiObjectiveCMAES implements InterfaceOptimizer, Serializable { * eva2.server.go.strategies.InterfaceOptimizer#SetProblem(eva2.server.go * .problems.InterfaceOptimizationProblem) */ - public void SetProblem(InterfaceOptimizationProblem problem) { + public void setProblem(InterfaceOptimizationProblem problem) { m_Problem = (AbstractOptimizationProblem) problem; } diff --git a/src/eva2/server/go/strategies/MultiObjectiveEA.java b/src/eva2/server/go/strategies/MultiObjectiveEA.java index 6e20d264..931b01e3 100644 --- a/src/eva2/server/go/strategies/MultiObjectiveEA.java +++ b/src/eva2/server/go/strategies/MultiObjectiveEA.java @@ -67,7 +67,7 @@ public class MultiObjectiveEA implements InterfaceOptimizer, java.io.Serializabl setArchivingStrategy(archiving); setArchiveSize(archiveSize); setInformationRetrieval(infoRetrieval); - SetProblem(problem); + setProblem(problem); } public Object clone() { @@ -171,9 +171,9 @@ public class MultiObjectiveEA implements InterfaceOptimizer, java.io.Serializabl /** This method will set the problem that is to be optimized * @param problem */ - public void SetProblem (InterfaceOptimizationProblem problem) { + public void setProblem (InterfaceOptimizationProblem problem) { this.m_Problem = problem; - this.m_Optimizer.SetProblem(problem); + this.m_Optimizer.setProblem(problem); } public InterfaceOptimizationProblem getProblem () { return this.m_Problem; diff --git a/src/eva2/server/go/strategies/NelderMeadSimplex.java b/src/eva2/server/go/strategies/NelderMeadSimplex.java index bb9587af..b8ee45c8 100644 --- a/src/eva2/server/go/strategies/NelderMeadSimplex.java +++ b/src/eva2/server/go/strategies/NelderMeadSimplex.java @@ -62,12 +62,12 @@ public class NelderMeadSimplex implements InterfaceOptimizer, Serializable, Inte m_Identifier = name; } - public void SetProblem(InterfaceOptimizationProblem problem) { + public void setProblem(InterfaceOptimizationProblem problem) { m_Problem = (AbstractOptimizationProblem)problem; } public boolean setProblemAndPopSize(InterfaceOptimizationProblem problem) { - SetProblem(problem); + setProblem(problem); if (m_Problem instanceof AbstractProblemDouble) { setPopulationSize(((AbstractProblemDouble)problem).getProblemDimension()+1); return true; diff --git a/src/eva2/server/go/strategies/NichePSO.java b/src/eva2/server/go/strategies/NichePSO.java index 9cff01ba..da6d9a26 100644 --- a/src/eva2/server/go/strategies/NichePSO.java +++ b/src/eva2/server/go/strategies/NichePSO.java @@ -256,7 +256,7 @@ public class NichePSO implements InterfaceAdditionalPopulationInformer, Interfac protected void initMainSwarm(){ // pass NichePSO parameter on to the mainswarmoptimzer setMainSwarmSize(mainSwarmSize); // (particles are initialized later via init) - getMainSwarm().SetProblem(m_Problem); + getMainSwarm().setProblem(m_Problem); getMainSwarm().SetMaxAllowedSwarmRadius(maxAllowedSwarmRadius); getMainSwarm().getPopulation().setGenerationTo(0); @@ -285,7 +285,7 @@ public class NichePSO implements InterfaceAdditionalPopulationInformer, Interfac */ protected void initSubswarmOptimizerTemplate(){ // pass on the parameters set via NichePSO (done in the analogous nichePSO-Setters as well -> no init() necessary) - getSubswarmOptimizerTemplate().SetProblem(m_Problem); + getSubswarmOptimizerTemplate().setProblem(m_Problem); getSubswarmOptimizerTemplate().SetMaxAllowedSwarmRadius(maxAllowedSwarmRadius); // choose PSO-type for the subswarmoptimizer @@ -311,7 +311,7 @@ public class NichePSO implements InterfaceAdditionalPopulationInformer, Interfac public ParticleSubSwarmOptimization getNewSubSwarmOptimizer(){ //initSubswarmOptimizerTemplate(); ParticleSubSwarmOptimization template = (ParticleSubSwarmOptimization)getSubswarmOptimizerTemplate().clone(); // this implicitely clones the problem but does not initialize it again... - template.SetProblem(this.m_Problem); //... let all subswarms use the same correct initialised problem instance + template.setProblem(this.m_Problem); //... let all subswarms use the same correct initialised problem instance return template; } @@ -1219,15 +1219,15 @@ public class NichePSO implements InterfaceAdditionalPopulationInformer, Interfac * This method will set the problem that is to be optimized * @param problem */ - public void SetProblem(InterfaceOptimizationProblem problem) { + public void setProblem(InterfaceOptimizationProblem problem) { // set member this.m_Problem = problem; // pass on to the main- and subswarm optimizers - getMainSwarm().SetProblem(problem); + getMainSwarm().setProblem(problem); for (int i = 0; i < getSubSwarms().size(); ++i){ - getSubSwarms().get(i).SetProblem(problem); + getSubSwarms().get(i).setProblem(problem); } - getSubswarmOptimizerTemplate().SetProblem(problem); + getSubswarmOptimizerTemplate().setProblem(problem); } /** @tested nn diff --git a/src/eva2/server/go/strategies/ParticleFilterOptimization.java b/src/eva2/server/go/strategies/ParticleFilterOptimization.java index 94038f4f..d443c834 100644 --- a/src/eva2/server/go/strategies/ParticleFilterOptimization.java +++ b/src/eva2/server/go/strategies/ParticleFilterOptimization.java @@ -257,7 +257,7 @@ public class ParticleFilterOptimization implements InterfaceOptimizer, java.io.S /** This method will set the problem that is to be optimized * @param problem */ - public void SetProblem (InterfaceOptimizationProblem problem) { + public void setProblem (InterfaceOptimizationProblem problem) { this.m_Problem = problem; if (problem instanceof AbstractOptimizationProblem) { ((AbstractOptimizationProblem)problem).informAboutOptimizer(this); diff --git a/src/eva2/server/go/strategies/ParticleSubSwarmOptimization.java b/src/eva2/server/go/strategies/ParticleSubSwarmOptimization.java index fde3d385..9eccbb92 100644 --- a/src/eva2/server/go/strategies/ParticleSubSwarmOptimization.java +++ b/src/eva2/server/go/strategies/ParticleSubSwarmOptimization.java @@ -456,7 +456,7 @@ public class ParticleSubSwarmOptimization extends ParticleSwarmOptimizationGCPSO /////////// ParticleSubSwarmOptimization tmpopt = new ParticleSubSwarmOptimization(); - tmpopt.SetProblem(this.m_Problem); + tmpopt.setProblem(this.m_Problem); tmpopt.evaluatePopulation(tmp); tmpopt.initByPopulation(tmp, false); // + size FCs @@ -558,7 +558,7 @@ public class ParticleSubSwarmOptimization extends ParticleSwarmOptimizationGCPSO * This method will set the problem that is to be optimized * @param problem */ - public void SetProblem (InterfaceOptimizationProblem problem) { + public void setProblem (InterfaceOptimizationProblem problem) { this.m_Problem = problem; updateMaxPosDist(); } diff --git a/src/eva2/server/go/strategies/ParticleSwarmOptimization.java b/src/eva2/server/go/strategies/ParticleSwarmOptimization.java index eb068af9..9157e9cb 100644 --- a/src/eva2/server/go/strategies/ParticleSwarmOptimization.java +++ b/src/eva2/server/go/strategies/ParticleSwarmOptimization.java @@ -1684,7 +1684,7 @@ public class ParticleSwarmOptimization implements InterfaceOptimizer, java.io.Se * * @param problem */ - public void SetProblem(InterfaceOptimizationProblem problem) { + public void setProblem(InterfaceOptimizationProblem problem) { this.m_Problem = problem; } diff --git a/src/eva2/server/go/strategies/PopulationBasedIncrementalLearning.java b/src/eva2/server/go/strategies/PopulationBasedIncrementalLearning.java index 62b366fc..d53ec71a 100644 --- a/src/eva2/server/go/strategies/PopulationBasedIncrementalLearning.java +++ b/src/eva2/server/go/strategies/PopulationBasedIncrementalLearning.java @@ -138,7 +138,7 @@ public class PopulationBasedIncrementalLearning implements InterfaceOptimizer, j /** This method will set the problem that is to be optimized * @param problem */ - public void SetProblem (InterfaceOptimizationProblem problem) { + public void setProblem (InterfaceOptimizationProblem problem) { this.m_Problem = problem; if (m_Problem instanceof AbstractOptimizationProblem) { if (!(((AbstractOptimizationProblem)m_Problem).getIndividualTemplate() instanceof InterfaceGAIndividual)) { diff --git a/src/eva2/server/go/strategies/ScatterSearch.java b/src/eva2/server/go/strategies/ScatterSearch.java index e312ba30..c3b56be5 100644 --- a/src/eva2/server/go/strategies/ScatterSearch.java +++ b/src/eva2/server/go/strategies/ScatterSearch.java @@ -104,7 +104,7 @@ public class ScatterSearch implements InterfaceOptimizer, java.io.Serializable, GenericObjectEditor.setHideProperty(this.getClass(), "population", true); } - public void SetProblem(InterfaceOptimizationProblem problem) { + public void setProblem(InterfaceOptimizationProblem problem) { this.problem = (AbstractOptimizationProblem)problem; } @@ -818,7 +818,7 @@ public class ScatterSearch implements InterfaceOptimizer, java.io.Serializable, AbstractOptimizationProblem problem, InterfaceTerminator term) { ScatterSearch ss = new ScatterSearch(); problem.initProblem(); - ss.SetProblem(problem); + ss.setProblem(problem); ss.setRefSetSize(refSetSize); ss.setNelderMeadInitPerturbation(nmInitPerturb); ss.setLocalSearchRelativeFilter(relativeFitCrit); diff --git a/src/eva2/server/go/strategies/SimulatedAnnealing.java b/src/eva2/server/go/strategies/SimulatedAnnealing.java index 5425d55f..357b6212 100644 --- a/src/eva2/server/go/strategies/SimulatedAnnealing.java +++ b/src/eva2/server/go/strategies/SimulatedAnnealing.java @@ -126,7 +126,7 @@ public class SimulatedAnnealing implements InterfaceOptimizer, java.io.Serializa /** This method will set the problem that is to be optimized * @param problem */ - public void SetProblem (InterfaceOptimizationProblem problem) { + public void setProblem (InterfaceOptimizationProblem problem) { this.m_Problem = problem; } public InterfaceOptimizationProblem getProblem () { diff --git a/src/eva2/server/go/strategies/SteadyStateGA.java b/src/eva2/server/go/strategies/SteadyStateGA.java index 76e8b3e7..458470fa 100644 --- a/src/eva2/server/go/strategies/SteadyStateGA.java +++ b/src/eva2/server/go/strategies/SteadyStateGA.java @@ -130,7 +130,7 @@ public class SteadyStateGA implements InterfaceOptimizer, java.io.Serializable { /** This method will set the problem that is to be optimized * @param problem */ - public void SetProblem (InterfaceOptimizationProblem problem) { + public void setProblem (InterfaceOptimizationProblem problem) { this.m_Problem = problem; } public InterfaceOptimizationProblem getProblem () { diff --git a/src/eva2/server/go/strategies/ThresholdAlgorithm.java b/src/eva2/server/go/strategies/ThresholdAlgorithm.java index a67a460c..f9ef12a1 100644 --- a/src/eva2/server/go/strategies/ThresholdAlgorithm.java +++ b/src/eva2/server/go/strategies/ThresholdAlgorithm.java @@ -118,7 +118,7 @@ public class ThresholdAlgorithm implements InterfaceOptimizer, java.io.Serializa /** This method will set the problem that is to be optimized * @param problem */ - public void SetProblem (InterfaceOptimizationProblem problem) { + public void setProblem (InterfaceOptimizationProblem problem) { this.m_Problem = problem; } public InterfaceOptimizationProblem getProblem () { diff --git a/src/eva2/server/go/strategies/Tribes.java b/src/eva2/server/go/strategies/Tribes.java index 1d01ab7c..c70da2a3 100644 --- a/src/eva2/server/go/strategies/Tribes.java +++ b/src/eva2/server/go/strategies/Tribes.java @@ -184,7 +184,7 @@ public class Tribes implements InterfaceOptimizer, java.io.Serializable { } public Tribes(Tribes other) { - this.SetProblem(other.getProblem()); + this.setProblem(other.getProblem()); iter = other.iter; setObjectiveFirstDim(other.getObjectiveFirstDim()); setDimension(other.range.length); @@ -202,7 +202,7 @@ public class Tribes implements InterfaceOptimizer, java.io.Serializable { hideHideable(); } - public void SetProblem(InterfaceOptimizationProblem problem) { + public void setProblem(InterfaceOptimizationProblem problem) { // System.out.println("TRIBES.SetProblem()"); m_problem = (AbstractOptimizationProblem)problem; range = null; diff --git a/src/eva2/server/go/strategies/WingedMultiObjectiveEA.java b/src/eva2/server/go/strategies/WingedMultiObjectiveEA.java index bd968a7d..731e2c41 100644 --- a/src/eva2/server/go/strategies/WingedMultiObjectiveEA.java +++ b/src/eva2/server/go/strategies/WingedMultiObjectiveEA.java @@ -66,7 +66,7 @@ public class WingedMultiObjectiveEA implements InterfaceOptimizer, java.io.Seria int dim = this.m_OutputDimension; double[] weights; // dim = tmpProb.getOutputDimension(); - this.m_MOOptimizer.SetProblem((InterfaceOptimizationProblem)this.m_Problem.clone()); + this.m_MOOptimizer.setProblem((InterfaceOptimizationProblem)this.m_Problem.clone()); this.m_MOOptimizer.init(); this.m_SOOptimizers = new InterfaceOptimizer[dim]; for (int i = 0; i < dim; i++) { @@ -79,11 +79,11 @@ public class WingedMultiObjectiveEA implements InterfaceOptimizer, java.io.Seria tmpWF.setWeights(tmpDA); tmpP.setMOSOConverter(tmpWF); this.m_SOOptimizers[i] = (InterfaceOptimizer)this.m_SOOptimizer.clone(); - this.m_SOOptimizers[i].SetProblem(tmpP); + this.m_SOOptimizers[i].setProblem(tmpP); this.m_SOOptimizers[i].init(); } } else { - this.m_SOOptimizer.SetProblem(this.m_Problem); + this.m_SOOptimizer.setProblem(this.m_Problem); this.m_SOOptimizer.init(); } this.communicate(); @@ -104,7 +104,7 @@ public class WingedMultiObjectiveEA implements InterfaceOptimizer, java.io.Seria int dim = 2; double[] weights; // dim = tmpProb.getOutputDimension(); - this.m_MOOptimizer.SetProblem((InterfaceOptimizationProblem)this.m_Problem.clone()); + this.m_MOOptimizer.setProblem((InterfaceOptimizationProblem)this.m_Problem.clone()); this.m_MOOptimizer.initByPopulation(pop, reset); this.m_SOOptimizers = new InterfaceOptimizer[dim]; for (int i = 0; i < dim; i++) { @@ -117,11 +117,11 @@ public class WingedMultiObjectiveEA implements InterfaceOptimizer, java.io.Seria tmpWF.setWeights(tmpDA); tmpP.setMOSOConverter(tmpWF); this.m_SOOptimizers[i] = (InterfaceOptimizer)this.m_SOOptimizer.clone(); - this.m_SOOptimizers[i].SetProblem(tmpP); + this.m_SOOptimizers[i].setProblem(tmpP); this.m_SOOptimizers[i].initByPopulation(pop, reset); } } else { - this.m_SOOptimizer.SetProblem(this.m_Problem); + this.m_SOOptimizer.setProblem(this.m_Problem); this.m_SOOptimizer.initByPopulation(pop, reset); } this.communicate(); @@ -224,7 +224,7 @@ public class WingedMultiObjectiveEA implements InterfaceOptimizer, java.io.Seria /** This method will set the problem that is to be optimized * @param problem */ - public void SetProblem (InterfaceOptimizationProblem problem) { + public void setProblem (InterfaceOptimizationProblem problem) { this.m_Problem = problem; } public InterfaceOptimizationProblem getProblem () { diff --git a/src/eva2/server/modules/AbstractGOParameters.java b/src/eva2/server/modules/AbstractGOParameters.java index f6d40458..8ce8e7f1 100644 --- a/src/eva2/server/modules/AbstractGOParameters.java +++ b/src/eva2/server/modules/AbstractGOParameters.java @@ -42,7 +42,7 @@ public abstract class AbstractGOParameters implements InterfaceGOParameters, Ser this.m_Optimizer = goParameters.m_Optimizer; this.m_Problem = goParameters.m_Problem; this.m_Terminator = goParameters.m_Terminator; - this.m_Optimizer.SetProblem(this.m_Problem); + this.m_Optimizer.setProblem(this.m_Problem); this.randomSeed = goParameters.randomSeed; this.m_PostProc = goParameters.m_PostProc; } @@ -53,7 +53,7 @@ public abstract class AbstractGOParameters implements InterfaceGOParameters, Ser m_Problem = prob; m_Terminator = term; m_PostProc = new PostProcessParams(false); - opt.SetProblem(prob); + opt.setProblem(prob); } /** @@ -65,7 +65,7 @@ public abstract class AbstractGOParameters implements InterfaceGOParameters, Ser setOptimizer(src.m_Optimizer); setProblem(src.m_Problem); setTerminator(src.m_Terminator); - this.m_Optimizer.SetProblem(this.m_Problem); + this.m_Optimizer.setProblem(this.m_Problem); setSeed(src.randomSeed); setPostProcessParams(src.m_PostProc); } @@ -139,7 +139,7 @@ public abstract class AbstractGOParameters implements InterfaceGOParameters, Ser public void setOptimizer(InterfaceOptimizer optimizer) { this.m_Optimizer = optimizer; - this.m_Optimizer.SetProblem(this.m_Problem); + this.m_Optimizer.setProblem(this.m_Problem); if (this.m_Listener != null) this.m_Optimizer.addPopulationChangedEventListener(this.m_Listener); fireNotifyOnInformers(); } @@ -168,7 +168,7 @@ public abstract class AbstractGOParameters implements InterfaceGOParameters, Ser */ public void setProblem (InterfaceOptimizationProblem problem) { this.m_Problem = problem; - this.m_Optimizer.SetProblem(this.m_Problem); + this.m_Optimizer.setProblem(this.m_Problem); fireNotifyOnInformers(); } diff --git a/src/eva2/server/modules/Processor.java b/src/eva2/server/modules/Processor.java index 02d41366..b22a74b0 100644 --- a/src/eva2/server/modules/Processor.java +++ b/src/eva2/server/modules/Processor.java @@ -230,7 +230,7 @@ public class Processor extends Thread implements InterfaceProcessor, InterfacePo m_Statistics.startOptPerformed(getInfoString(), runCounter, goParams, getInformerList()); this.goParams.getProblem().initProblem(); - this.goParams.getOptimizer().SetProblem(this.goParams.getProblem()); + this.goParams.getOptimizer().setProblem(this.goParams.getProblem()); this.goParams.getTerminator().init(this.goParams.getProblem()); maybeInitParamCtrl(goParams); if (this.m_createInitialPopulations) {