#region License Information
/* HeuristicLab
* Copyright (C) 2002-2019 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
*
* This file is part of HeuristicLab.
*
* HeuristicLab is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* HeuristicLab is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with HeuristicLab. If not, see .
*/
#endregion
using System.IO;
using HeuristicLab.Algorithms.EvolutionStrategy;
using HeuristicLab.Data;
using HeuristicLab.Encodings.RealVectorEncoding;
using HeuristicLab.Persistence.Default.Xml;
using HeuristicLab.Problems.TestFunctions;
using Microsoft.VisualStudio.TestTools.UnitTesting;
namespace HeuristicLab.Tests {
[TestClass]
public class EsGriewankSampleTest {
private const string SampleFileName = "ES_Griewank";
[TestMethod]
[TestCategory("Samples.Create")]
[TestProperty("Time", "medium")]
public void CreateEsGriewankSampleTest() {
var es = CreateEsGriewankSample();
string path = Path.Combine(SamplesUtils.SamplesDirectory, SampleFileName + SamplesUtils.SampleFileExtension);
XmlGenerator.Serialize(es, path);
}
[TestMethod]
[TestCategory("Samples.Execute")]
[TestProperty("Time", "long")]
public void RunEsGriewankSampleTest() {
var es = CreateEsGriewankSample();
es.SetSeedRandomly.Value = false;
SamplesUtils.RunAlgorithm(es);
Assert.AreEqual(0, SamplesUtils.GetDoubleResult(es, "BestQuality"));
Assert.AreEqual(0, SamplesUtils.GetDoubleResult(es, "CurrentAverageQuality"));
Assert.AreEqual(0, SamplesUtils.GetDoubleResult(es, "CurrentWorstQuality"));
Assert.AreEqual(100020, SamplesUtils.GetIntResult(es, "EvaluatedSolutions"));
}
private EvolutionStrategy CreateEsGriewankSample() {
EvolutionStrategy es = new EvolutionStrategy();
#region Problem Configuration
SingleObjectiveTestFunctionProblem problem = new SingleObjectiveTestFunctionProblem();
problem.ProblemSize.Value = 10;
problem.EvaluatorParameter.Value = new GriewankEvaluator();
problem.SolutionCreatorParameter.Value = new UniformRandomRealVectorCreator();
problem.Maximization.Value = false;
problem.Bounds = new DoubleMatrix(new double[,] { { -600, 600 } });
problem.BestKnownQuality.Value = 0;
problem.BestKnownSolutionParameter.Value = new RealVector(10);
problem.Name = "Single Objective Test Function";
problem.Description = "Test function with real valued inputs and a single objective.";
#endregion
#region Algorithm Configuration
es.Name = "Evolution Strategy - Griewank";
es.Description = "An evolution strategy which solves the 10-dimensional Griewank test function";
es.Problem = problem;
SamplesUtils.ConfigureEvolutionStrategyParameters(
es, 20, 500, 2, 200, false);
StdDevStrategyVectorCreator strategyCreator = (StdDevStrategyVectorCreator)es.StrategyParameterCreator;
strategyCreator.BoundsParameter.Value = new DoubleMatrix(new double[,] { { 1, 20 } });
StdDevStrategyVectorManipulator strategyManipulator =
(StdDevStrategyVectorManipulator)es.StrategyParameterManipulator;
strategyManipulator.BoundsParameter.Value = new DoubleMatrix(new double[,] { { 1E-12, 30 } });
strategyManipulator.GeneralLearningRateParameter.Value = new DoubleValue(0.22360679774997896);
strategyManipulator.LearningRateParameter.Value = new DoubleValue(0.39763536438352531);
#endregion
return es;
}
}
}