[13412] | 1 | #region License Information
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| 2 | /* HeuristicLab
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| 3 | * Copyright (C) 2002-2015 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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| 4 | *
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| 5 | * This file is part of HeuristicLab.
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| 6 | *
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| 7 | * HeuristicLab is free software: you can redistribute it and/or modify
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| 8 | * it under the terms of the GNU General Public License as published by
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| 9 | * the Free Software Foundation, either version 3 of the License, or
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| 10 | * (at your option) any later version.
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| 11 | *
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| 12 | * HeuristicLab is distributed in the hope that it will be useful,
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| 13 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
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| 14 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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| 15 | * GNU General Public License for more details.
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| 16 | *
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| 17 | * You should have received a copy of the GNU General Public License
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| 18 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
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| 19 | */
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| 20 | #endregion
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| 21 |
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| 22 | using HeuristicLab.Common;
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[12191] | 23 | using HeuristicLab.Core;
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[13412] | 24 | using HeuristicLab.Data;
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| 25 | using HeuristicLab.Encodings.PermutationEncoding;
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[12191] | 26 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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| 27 |
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| 28 | namespace HeuristicLab.Problems.PTSP {
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[13412] | 29 | [Item("Analytical Probabilistic Traveling Salesman Problem (PTSP)", "Represents a probabilistic traveling salesman problem where the expected tour length is calculated exactly.")]
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| 30 | [Creatable(CreatableAttribute.Categories.CombinatorialProblems)]
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[12191] | 31 | [StorableClass]
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[13412] | 32 | public sealed class AnalyticalProbabilisticTravelingSalesmanProblem : ProbabilisticTravelingSalesmanProblem {
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[12191] | 33 |
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| 34 | [StorableConstructor]
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| 35 | private AnalyticalProbabilisticTravelingSalesmanProblem(bool deserializing) : base(deserializing) { }
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[13412] | 36 | private AnalyticalProbabilisticTravelingSalesmanProblem(AnalyticalProbabilisticTravelingSalesmanProblem original, Cloner cloner) : base(original, cloner) { }
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| 37 | public AnalyticalProbabilisticTravelingSalesmanProblem() {
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| 38 | Operators.Add(new BestPTSPSolutionAnalyzer());
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[12191] | 39 | }
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| 40 |
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| 41 | public override IDeepCloneable Clone(Cloner cloner) {
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| 42 | return new AnalyticalProbabilisticTravelingSalesmanProblem(this, cloner);
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| 43 | }
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| 44 |
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[13412] | 45 | public override double Evaluate(Permutation tour, IRandom random) {
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[12191] | 46 | // Analytical evaluation
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| 47 | double firstSum = 0;
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[13412] | 48 | for (int i = 0; i < tour.Length - 1; i++) {
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| 49 | for (int j = i + 1; j < tour.Length - 1; j++) {
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| 50 | double sum1 = DistanceMatrix[tour[i], tour[j]] * Probabilities[tour[i]] * Probabilities[tour[j]];
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[12191] | 51 | for (int k = i + 1; k < j; k++) {
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[13412] | 52 | sum1 = sum1 * (1 - Probabilities[tour[k]]);
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[12191] | 53 | }
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| 54 | firstSum += sum1;
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| 55 | }
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| 56 | }
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| 57 | double secondSum = 0;
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[13412] | 58 | for (int j = 0; j < tour.Length - 1; j++) {
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[12191] | 59 | for (int i = 0; i < j; i++) {
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[13412] | 60 | double sum2 = DistanceMatrix[tour[j], tour[i]] * Probabilities[tour[i]] * Probabilities[tour[j]];
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| 61 | for (int k = j + 1; k < tour.Length - 1; k++) {
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| 62 | sum2 = sum2 * (1 - Probabilities[tour[k]]);
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[12191] | 63 | }
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| 64 | for (int k = 1; k < i; k++) {
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[13412] | 65 | sum2 = sum2 * (1 - Probabilities[tour[k]]);
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[12191] | 66 | }
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| 67 | secondSum += sum2;
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| 68 | }
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| 69 | }
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| 70 | return firstSum + secondSum;
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| 71 | }
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| 72 |
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[13412] | 73 | public static double Evaluate(Permutation tour, DistanceMatrix distanceMatrix, DoubleArray probabilities) {
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[12269] | 74 | // Analytical evaluation
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[13412] | 75 | var firstSum = 0.0;
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| 76 | for (var i = 0; i < tour.Length; i++) {
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| 77 | for (var j = i + 1; j < tour.Length; j++) {
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| 78 | var sum1 = distanceMatrix[tour[i], tour[j]] * probabilities[tour[i]] * probabilities[tour[j]];
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| 79 | for (var k = i + 1; k < j; k++) {
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| 80 | sum1 = sum1 * (1 - probabilities[tour[k]]);
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[12269] | 81 | }
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| 82 | firstSum += sum1;
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| 83 | }
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| 84 | }
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[13412] | 85 | var secondSum = 0.0;
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| 86 | for (var j = 0; j < tour.Length; j++) {
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| 87 | for (var i = 0; i < j; i++) {
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| 88 | var sum2 = distanceMatrix[tour[j], tour[i]] * probabilities[tour[i]] * probabilities[tour[j]];
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| 89 | for (var k = j + 1; k < tour.Length; k++) {
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| 90 | sum2 = sum2 * (1 - probabilities[tour[k]]);
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[12269] | 91 | }
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[13412] | 92 | for (var k = 0; k < i; k++) {
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| 93 | sum2 = sum2 * (1 - probabilities[tour[k]]);
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[12269] | 94 | }
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| 95 | secondSum += sum2;
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| 96 | }
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| 97 | }
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| 98 | return firstSum + secondSum;
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| 99 | }
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[12191] | 100 | }
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| 101 | }
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