#region License Information
/* HeuristicLab
* Copyright (C) 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;
}
}
}
}