#region License Information /* HeuristicLab * Copyright (C) 2002-2015 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; using HeuristicLab.Common; using HeuristicLab.Core; using HeuristicLab.Data; using HeuristicLab.Encodings.PermutationEncoding; using HeuristicLab.Random; using Microsoft.VisualStudio.TestTools.UnitTesting; namespace HeuristicLab.Problems.PTSP.Tests { /// ///This is a test class for PTSP move evaluators /// [TestClass()] public class PTSPMoveEvaluatorTest { private const int ProblemSize = 10; private const int RealizationsSize = 100; private static DoubleMatrix coordinates; private static DistanceMatrix distances; private static Permutation tour; private static MersenneTwister random; private static ItemList realizations; private static DoubleArray probabilities; [ClassInitialize] public static void MyClassInitialize(TestContext testContext) { random = new MersenneTwister(); coordinates = new DoubleMatrix(ProblemSize, 2); distances = new DistanceMatrix(ProblemSize, ProblemSize); for (var i = 0; i < ProblemSize; i++) { coordinates[i, 0] = random.Next(ProblemSize * 10); coordinates[i, 1] = random.Next(ProblemSize * 10); } for (var i = 0; i < ProblemSize - 1; i++) { for (var j = i + 1; j < ProblemSize; j++) { distances[i, j] = Math.Round(Math.Sqrt(Math.Pow(coordinates[i, 0] - coordinates[j, 0], 2) + Math.Pow(coordinates[i, 1] - coordinates[j, 1], 2))); distances[j, i] = distances[i, j]; } } probabilities = new DoubleArray(ProblemSize); for (var i = 0; i < ProblemSize; i++) { probabilities[i] = random.NextDouble(); } realizations = new ItemList(RealizationsSize); for (var i = 0; i < RealizationsSize; i++) { var countOnes = 0; var newRealization = new BoolArray(ProblemSize); while (countOnes < 4) { //only generate realizations with at least 4 cities visited countOnes = 0; for (var j = 0; j < ProblemSize; j++) { newRealization[j] = random.NextDouble() < probabilities[j]; if (newRealization[j]) countOnes++; } } realizations.Add(newRealization); } tour = new Permutation(PermutationTypes.RelativeUndirected, ProblemSize, random); } [TestMethod] [TestCategory("Problems.ProbabilisticTravelingSalesman")] [TestProperty("Time", "short")] public void InversionMoveEvaluatorTest() { Func distance = (a, b) => distances[a, b]; double variance; var beforeMatrix = EstimatedProbabilisticTravelingSalesmanProblem.Evaluate(tour, distance, realizations, out variance); for (var i = 0; i < 500; i++) { var move = StochasticInversionSingleMoveGenerator.Apply(tour, random); var moveMatrix = PTSPEstimatedInversionMoveEvaluator.EvaluateMove(tour, move, distance, realizations); InversionManipulator.Apply(tour, move.Index1, move.Index2); var afterMatrix = EstimatedProbabilisticTravelingSalesmanProblem.Evaluate(tour, distance, realizations, out variance); Assert.IsTrue(Math.Abs(moveMatrix).IsAlmost(Math.Abs(afterMatrix - beforeMatrix)), string.Format(@"Inversion move is calculated with quality {0}, but actual difference is {4}. The move would invert the tour {1} between values {2} and {3}.", moveMatrix, tour, tour[move.Index1], tour[move.Index2], Math.Abs(afterMatrix - beforeMatrix))); beforeMatrix = afterMatrix; } } [TestMethod] [TestCategory("Problems.ProbabilisticTravelingSalesman")] [TestProperty("Time", "short")] public void InsertionMoveEvaluatorTest() { Func distance = (a, b) => distances[a, b]; double variance; var beforeMatrix = EstimatedProbabilisticTravelingSalesmanProblem.Evaluate(tour, distance, realizations, out variance); for (var i = 0; i < 500; i++) { var move = StochasticTranslocationSingleMoveGenerator.Apply(tour, random); var moveMatrix = PTSPEstimatedInsertionMoveEvaluator.EvaluateMove(tour, move, distance, realizations); TranslocationManipulator.Apply(tour, move.Index1, move.Index1, move.Index3); var afterMatrix = EstimatedProbabilisticTravelingSalesmanProblem.Evaluate(tour, distance, realizations, out variance); Assert.IsTrue(Math.Abs(moveMatrix).IsAlmost(Math.Abs(afterMatrix - beforeMatrix)), string.Format(@"Insertion move is calculated with quality {0}, but actual difference is {4}. The move would invert the tour {1} between values {2} and {3}.", moveMatrix, tour, tour[move.Index1], tour[move.Index2], Math.Abs(afterMatrix - beforeMatrix))); beforeMatrix = afterMatrix; } } } }