#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; } } }