#region License Information /* HeuristicLab * Copyright (C) 2002-2014 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 System.Linq; using HeuristicLab.Algorithms.GeneticAlgorithm; using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding; using HeuristicLab.Persistence.Default.Xml; using HeuristicLab.Problems.ArtificialAnt; using HeuristicLab.Selection; using Microsoft.VisualStudio.TestTools.UnitTesting; namespace HeuristicLab.Tests { [TestClass] public class GPArtificialAntSampleTest { private const string SampleFileName = "SGP_SantaFe"; [TestMethod] [TestCategory("Samples.Create")] [TestProperty("Time", "medium")] public void CreateGpArtificialAntSampleTest() { var ga = CreateGpArtificialAntSample(); string path = Path.Combine(SamplesUtils.SamplesDirectory, SampleFileName + SamplesUtils.SampleFileExtension); XmlGenerator.Serialize(ga, path); } [TestMethod] [TestCategory("Samples.Execute")] [TestProperty("Time", "long")] public void RunGpArtificialAntSampleTest() { var ga = CreateGpArtificialAntSample(); ga.SetSeedRandomly.Value = false; SamplesUtils.RunAlgorithm(ga); Assert.AreEqual(81, SamplesUtils.GetDoubleResult(ga, "BestQuality")); Assert.AreEqual(48.19, SamplesUtils.GetDoubleResult(ga, "CurrentAverageQuality")); Assert.AreEqual(0, SamplesUtils.GetDoubleResult(ga, "CurrentWorstQuality")); Assert.AreEqual(50950, SamplesUtils.GetIntResult(ga, "EvaluatedSolutions")); } public GeneticAlgorithm CreateGpArtificialAntSample() { GeneticAlgorithm ga = new GeneticAlgorithm(); #region Problem Configuration ArtificialAntProblem antProblem = new ArtificialAntProblem(); antProblem.BestKnownQuality.Value = 89; antProblem.MaxExpressionDepth.Value = 10; antProblem.MaxExpressionLength.Value = 100; antProblem.MaxFunctionArguments.Value = 3; antProblem.MaxFunctionDefinitions.Value = 3; antProblem.MaxTimeSteps.Value = 600; #endregion #region Algorithm Configuration ga.Name = "Genetic Programming - Artificial Ant"; ga.Description = "A standard genetic programming algorithm to solve the artificial ant problem (Santa-Fe trail)"; ga.Problem = antProblem; SamplesUtils.ConfigureGeneticAlgorithmParameters( ga, 1000, 1, 50, 0.15, 5); var mutator = (MultiSymbolicExpressionTreeArchitectureManipulator)ga.Mutator; mutator.Operators.SetItemCheckedState(mutator.Operators .OfType() .Single(), false); mutator.Operators.SetItemCheckedState(mutator.Operators .OfType() .Single(), false); mutator.Operators.SetItemCheckedState(mutator.Operators .OfType() .Single(), false); mutator.Operators.SetItemCheckedState(mutator.Operators .OfType() .Single(), false); #endregion return ga; } } }