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May 25, 2019 03:59
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package hu.bme.mit.inf.dslreasoner.domains.cps.mdeo | |
import java.util.Properties | |
import org.moeaframework.Executor | |
import org.moeaframework.Instrumenter | |
import org.moeaframework.algorithm.PeriodicAction | |
import org.moeaframework.core.TerminationCondition | |
import org.moeaframework.core.spi.AlgorithmFactory | |
import uk.ac.kcl.inf.mdeoptimiser.interfaces.cli.Run | |
import uk.ac.kcl.inf.mdeoptimiser.languages.mopt.Optimisation | |
import uk.ac.kcl.inf.mdeoptimiser.languages.mopt.SolverSpec | |
import uk.ac.kcl.inf.mdeoptimiser.libraries.core.optimisation.OptimisationInterpreter | |
import uk.ac.kcl.inf.mdeoptimiser.libraries.core.optimisation.executor.SolutionGenerator | |
import uk.ac.kcl.inf.mdeoptimiser.libraries.core.optimisation.moea.MoeaOptimisation | |
import uk.ac.kcl.inf.mdeoptimiser.libraries.core.optimisation.moea.algorithms.MoeaOptimisationAlgorithmProvider | |
import uk.ac.kcl.inf.mdeoptimiser.libraries.core.optimisation.moea.instrumentation.PopulationCollector | |
import uk.ac.kcl.inf.mdeoptimiser.libraries.core.optimisation.moea.problem.MoeaOptimisationProblem | |
import uk.ac.kcl.inf.mdeoptimiser.libraries.core.optimisation.operators.adaptation.MutationStepSizeStrategyFactory | |
import uk.ac.kcl.inf.mdeoptimiser.libraries.core.optimisation.output.MDEOBatch | |
class ExcludedMoeaOptimisation extends MoeaOptimisation { | |
SolutionGenerator solutionGenerator | |
Instrumenter algorithmStepSizeInstrumenter | |
override execute(SolverSpec solverSpec, SolutionGenerator solutionGenerator) { | |
this.solutionGenerator = solutionGenerator | |
super.execute(solverSpec, solutionGenerator) | |
} | |
override Instrumenter runOptimisation(SolverSpec solverSpec, Properties optimisationProperties) { | |
val algorithmFactory = new AlgorithmFactory | |
algorithmFactory.addProvider(new MoeaOptimisationAlgorithmProvider) | |
algorithmStepSizeInstrumenter = new Instrumenter().addExcludedPackage("org.eclipse").withProblemClass( | |
MoeaOptimisationProblem, solutionGenerator).attachApproximationSetCollector().attachElapsedTimeCollector(). | |
attachPopulationSizeCollector.attach(new PopulationCollector()).withFrequency(1).withFrequencyType( | |
PeriodicAction.FrequencyType.STEPS) | |
var stepSizeStrategy = new MutationStepSizeStrategyFactory(solverSpec.algorithm, algorithmStepSizeInstrumenter). | |
strategy | |
solutionGenerator.setMutationStepSizeStrategy(stepSizeStrategy) | |
// TODO: Place this in a better location. | |
// Exclude JDK packages from Instrumenter | |
this.algorithmStepSizeInstrumenter.addExcludedPackage("jdk") | |
new Executor().usingAlgorithmFactory(algorithmFactory).withAlgorithm(solverSpec.algorithm.name) // Initialize problem with our solution generator | |
.withProblemClass(MoeaOptimisationProblem, solutionGenerator).withProperties(optimisationProperties). | |
withInstrumenter(algorithmStepSizeInstrumenter).withTerminationCondition( | |
optimisationProperties.get("terminationCondition") as TerminationCondition).run() | |
return algorithmStepSizeInstrumenter | |
} | |
} | |
class ExcludedOptimisationInterpreter extends OptimisationInterpreter { | |
val Optimisation model | |
new(String projectPath, Optimisation model) { | |
super(projectPath, model) | |
this.model = model | |
} | |
override start() { | |
// This model provider loads the model given by the user in the DSL | |
var solutionGenerator = new SolutionGenerator(model, getBreedingOperators, getMutationOperators, | |
getModelProvider, getMetamodel); | |
return new ExcludedMoeaOptimisation().execute(model.solver, solutionGenerator) | |
} | |
} | |
class ExcludedRun extends Run { | |
override runBatch(String moptProjectPath, Optimisation optimisationModel, Integer batch, boolean singleBatch) { | |
val optimisationInterpreter = new ExcludedOptimisationInterpreter(moptProjectPath, optimisationModel); | |
val startTime = System.nanoTime(); | |
val optimisationOutcome = optimisationInterpreter.start(); | |
val endTime = System.nanoTime(); | |
val experimentDuration = ((endTime - startTime) / 1000000); | |
val generatedRules = optimisationInterpreter.getRulegenOperators(); | |
return new MDEOBatch(batch, experimentDuration, optimisationOutcome, generatedRules, singleBatch); | |
} | |
} |
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