[11191] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[16565] | 3 | * Copyright (C) 2002-2019 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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[11191] | 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 System.Collections.Generic;
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| 23 | using System.Linq;
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| 24 | using HeuristicLab.Common;
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| 25 | using HeuristicLab.Core;
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| 26 | using HeuristicLab.Data;
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| 27 | using HeuristicLab.Encodings.IntegerVectorEncoding;
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| 28 | using HeuristicLab.Parameters;
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[16565] | 29 | using HEAL.Attic;
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[11191] | 30 |
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| 31 | namespace HeuristicLab.Problems.Orienteering {
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[12721] | 32 | /// <summary>
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| 33 | /// The initial solution for P-VNS is generated by means of a greedy algorithm that takes into
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| 34 | /// account all vertices vi that are located within the cost limit Tmax. These points are sorted
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| 35 | /// in descending order regarding the sum of their objective values. Afterwards, the algorithm
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| 36 | /// starts with a tour only including the starting and ending point and successively inserts the
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| 37 | /// points from this list at the first position in which they can feasibly be inserted.
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| 38 | /// (Schilde et. al. 2009)
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| 39 | /// </summary>
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| 40 | [Item("GreedyOrienteeringTourCreator", @"Implements the solution creation procedure described in Schilde M., Doerner K.F., Hartl R.F., Kiechle G. 2009. Metaheuristics for the bi-objective orienteering problem. Swarm Intelligence, Volume 3, Issue 3, pp 179-201.")]
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[16565] | 41 | [StorableType("FB68525D-DD53-4BE7-A6B4-EC54E6FD0E64")]
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[11321] | 42 | public sealed class GreedyOrienteeringTourCreator : IntegerVectorCreator, IOrienteeringSolutionCreator {
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[11191] | 43 | public override bool CanChangeName { get { return false; } }
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| 44 |
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| 45 | #region Parameter Properties
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| 46 | public ILookupParameter<DistanceMatrix> DistanceMatrixParameter {
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| 47 | get { return (ILookupParameter<DistanceMatrix>)Parameters["DistanceMatrix"]; }
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| 48 | }
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| 49 | public ILookupParameter<DoubleArray> ScoresParameter {
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| 50 | get { return (ILookupParameter<DoubleArray>)Parameters["Scores"]; }
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| 51 | }
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| 52 | public ILookupParameter<DoubleValue> MaximumDistanceParameter {
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| 53 | get { return (ILookupParameter<DoubleValue>)Parameters["MaximumDistance"]; }
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| 54 | }
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| 55 | public ILookupParameter<IntValue> StartingPointParameter {
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| 56 | get { return (ILookupParameter<IntValue>)Parameters["StartingPoint"]; }
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| 57 | }
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[11319] | 58 | public ILookupParameter<IntValue> TerminalPointParameter {
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| 59 | get { return (ILookupParameter<IntValue>)Parameters["TerminalPoint"]; }
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[11191] | 60 | }
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[11320] | 61 | public ILookupParameter<DoubleValue> PointVisitingCostsParameter {
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| 62 | get { return (ILookupParameter<DoubleValue>)Parameters["PointVisitingCosts"]; }
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[11191] | 63 | }
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| 64 | #endregion
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| 65 |
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| 66 | [StorableConstructor]
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[16565] | 67 | private GreedyOrienteeringTourCreator(StorableConstructorFlag _) : base(_) { }
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[11307] | 68 | private GreedyOrienteeringTourCreator(GreedyOrienteeringTourCreator original, Cloner cloner)
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[11191] | 69 | : base(original, cloner) { }
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| 70 |
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| 71 | public GreedyOrienteeringTourCreator()
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| 72 | : base() {
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| 73 | Parameters.Add(new LookupParameter<DistanceMatrix>("DistanceMatrix", "The matrix which contains the distances between the points."));
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| 74 | Parameters.Add(new LookupParameter<DoubleArray>("Scores", "The scores of the points."));
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| 75 | Parameters.Add(new LookupParameter<DoubleValue>("MaximumDistance", "The maximum distance constraint for a Orienteering solution."));
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| 76 | Parameters.Add(new LookupParameter<IntValue>("StartingPoint", "Index of the starting point."));
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[11319] | 77 | Parameters.Add(new LookupParameter<IntValue>("TerminalPoint", "Index of the ending point."));
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[11320] | 78 | Parameters.Add(new LookupParameter<DoubleValue>("PointVisitingCosts", "The costs for visiting a point."));
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[11191] | 79 | }
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| 80 |
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| 81 | public override IDeepCloneable Clone(Cloner cloner) {
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| 82 | return new GreedyOrienteeringTourCreator(this, cloner);
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| 83 | }
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| 84 |
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[12721] | 85 | protected override IntegerVector Create(IRandom random, IntValue length, IntMatrix bounds) {
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[11191] | 86 | int startPoint = StartingPointParameter.ActualValue.Value;
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[11319] | 87 | int endPoint = TerminalPointParameter.ActualValue.Value;
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[11191] | 88 | int numPoints = ScoresParameter.ActualValue.Length;
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| 89 | var distances = DistanceMatrixParameter.ActualValue;
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[11320] | 90 | double pointVisitingCosts = PointVisitingCostsParameter.ActualValue.Value;
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[11191] | 91 | double maxDistance = MaximumDistanceParameter.ActualValue.Value;
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| 92 | var scores = ScoresParameter.ActualValue;
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| 93 |
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| 94 | // Find all points within the maximum distance allowed (ellipse)
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[11228] | 95 | var feasiblePoints = (
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| 96 | from point in Enumerable.Range(0, numPoints)
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[11320] | 97 | let distance = distances[startPoint, point] + distances[point, endPoint] + pointVisitingCosts
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[11228] | 98 | let score = scores[point]
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| 99 | where distance <= maxDistance
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| 100 | where point != startPoint && point != endPoint
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| 101 | orderby score descending
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| 102 | select point
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| 103 | ).ToList();
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[11191] | 104 |
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| 105 | // Add the starting and terminus point
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| 106 | var tour = new List<int> {
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| 107 | startPoint,
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| 108 | endPoint
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| 109 | };
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[12721] | 110 | double tourLength = distances[startPoint, endPoint];
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[11191] | 111 |
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| 112 | // Add points in a greedy way
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| 113 | bool insertionPerformed = true;
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| 114 | while (insertionPerformed) {
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| 115 | insertionPerformed = false;
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| 116 |
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[11228] | 117 | for (int i = 0; i < feasiblePoints.Count; i++) {
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[11192] | 118 | for (int insertPosition = 1; insertPosition < tour.Count; insertPosition++) {
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[11191] | 119 | // Create the candidate tour
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[11320] | 120 | double detour = distances.CalculateInsertionCosts(tour, insertPosition, feasiblePoints[i], pointVisitingCosts);
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[11191] | 121 |
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| 122 | // If the insertion would be feasible, perform it
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[12721] | 123 | if (tourLength + detour <= maxDistance) {
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[11228] | 124 | tour.Insert(insertPosition, feasiblePoints[i]);
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[12721] | 125 | tourLength += detour;
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[11228] | 126 | feasiblePoints.RemoveAt(i);
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[11191] | 127 | insertionPerformed = true;
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| 128 | break;
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| 129 | }
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| 130 | }
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| 131 | if (insertionPerformed) break;
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| 132 | }
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| 133 | }
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| 134 |
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| 135 | return new IntegerVector(tour.ToArray());
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| 136 | }
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| 137 | }
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| 138 | } |
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