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@ -56,6 +56,7 @@ import eva2.server.go.strategies.PopulationBasedIncrementalLearning;
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import eva2.server.go.strategies.SimulatedAnnealing;
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import eva2.server.go.strategies.SimulatedAnnealing;
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import eva2.server.go.strategies.Tribes;
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import eva2.server.go.strategies.Tribes;
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import eva2.server.modules.GOParameters;
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import eva2.server.modules.GOParameters;
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import eva2.server.stat.InterfaceStatistics;
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/**
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/**
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* <p>
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* <p>
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@ -868,6 +869,12 @@ public class OptimizerFactory {
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return runnable.getDoubleSolution();
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return runnable.getDoubleSolution();
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}
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}
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public static double[] optimizeToDouble(GOParameters params,InterfaceStatistics stats) {
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OptimizerRunnable runnable = optimize(new OptimizerRunnable(params,stats,
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false));
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return runnable.getDoubleSolution();
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}
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public static double[] optimizeToDouble(final int optType,
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public static double[] optimizeToDouble(final int optType,
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AbstractOptimizationProblem problem, String outputFilePrefix) {
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AbstractOptimizationProblem problem, String outputFilePrefix) {
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OptimizerRunnable runnable = optimize(optType, problem,
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OptimizerRunnable runnable = optimize(optType, problem,
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@ -880,6 +887,8 @@ public class OptimizerFactory {
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return (runnable != null) ? runnable.getDoubleSolution() : null;
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return (runnable != null) ? runnable.getDoubleSolution() : null;
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}
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}
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public static IndividualInterface optimizeToInd(GOParameters params,
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public static IndividualInterface optimizeToInd(GOParameters params,
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String outputFilePrefix) {
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String outputFilePrefix) {
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OptimizerRunnable runnable = optimize(new OptimizerRunnable(params,
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OptimizerRunnable runnable = optimize(new OptimizerRunnable(params,
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