#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 System.Collections.Generic; using System.Linq; using System.Text; using System.Threading.Tasks; using HeuristicLab.Optimization; using HeuristicLab.PluginInfrastructure; using HeuristicLab.Core; using HeuristicLab.Persistence.Default.CompositeSerializers.Storable; using HeuristicLab.Problems.Instances; using HeuristicLab.Encodings.PermutationEncoding; using HeuristicLab.Common; using HeuristicLab.Parameters; using HeuristicLab.Data; using HeuristicLab.Random; namespace HeuristicLab.Problems.PTSP { [Item("Probabilistic Traveling Salesman Problem", "Represents a Probabilistic Traveling Salesman Problem.")] [StorableClass] public abstract class ProbabilisticTravelingSalesmanProblem : SingleObjectiveBasicProblem, IStorableContent, IProblemInstanceConsumer { private static readonly int DistanceMatrixSizeLimit = 1000; #region Parameter Properties public OptionalValueParameter CoordinatesParameter { get { return (OptionalValueParameter)Parameters["Coordinates"]; } } public OptionalValueParameter DistanceMatrixParameter { get { return (OptionalValueParameter)Parameters["DistanceMatrix"]; } } public ValueParameter UseDistanceMatrixParameter { get { return (ValueParameter)Parameters["UseDistanceMatrix"]; } } public OptionalValueParameter BestKnownSolutionParameter { get { return (OptionalValueParameter)Parameters["BestKnownSolution"]; } } public ValueParameter ProbabilityMatrixParameter { get { return (ValueParameter)Parameters["ProbabilityMatrix"]; } } #endregion #region Properties public DoubleMatrix Coordinates { get { return CoordinatesParameter.Value; } set { CoordinatesParameter.Value = value; } } public DistanceMatrix DistanceMatrix { get { return DistanceMatrixParameter.Value; } set { DistanceMatrixParameter.Value = value; } } public BoolValue UseDistanceMatrix { get { return UseDistanceMatrixParameter.Value; } set { UseDistanceMatrixParameter.Value = value; } } public Permutation BestKnownSolution { get { return BestKnownSolutionParameter.Value; } set { BestKnownSolutionParameter.Value = value; } } public DoubleArray ProbabilityMatrix { get { return ProbabilityMatrixParameter.Value; } set { ProbabilityMatrixParameter.Value = value; } } #endregion public override bool Maximization { get { return false; } } [StorableConstructor] protected ProbabilisticTravelingSalesmanProblem(bool deserializing) : base(deserializing) { } protected ProbabilisticTravelingSalesmanProblem(ProbabilisticTravelingSalesmanProblem original, Cloner cloner) : base(original, cloner) { } public ProbabilisticTravelingSalesmanProblem() { Parameters.Add(new OptionalValueParameter("Coordinates", "The x- and y-Coordinates of the cities.")); Parameters.Add(new OptionalValueParameter("DistanceMatrix", "The matrix which contains the distances between the cities.")); Parameters.Add(new ValueParameter("UseDistanceMatrix", "True if the coordinates based evaluators should calculate the distance matrix from the coordinates and use it for evaluation similar to the distance matrix evaluator, otherwise false.", new BoolValue(true))); Parameters.Add(new OptionalValueParameter("BestKnownSolution", "The best known solution of this TSP instance.")); Parameters.Add(new ValueParameter("ProbabilityMatrix", "The matrix which contains the probabilities of each of the cities.")); Coordinates = new DoubleMatrix(new double[,] { { 100, 100 }, { 100, 200 }, { 100, 300 }, { 100, 400 }, { 200, 100 }, { 200, 200 }, { 200, 300 }, { 200, 400 }, { 300, 100 }, { 300, 200 }, { 300, 300 }, { 300, 400 }, { 400, 100 }, { 400, 200 }, { 400, 300 }, { 400, 400 } }); ProbabilityMatrix = new DoubleArray(new double[] {1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1}); } public virtual void Load(PTSPData data) { if (data.Coordinates == null && data.Distances == null) throw new System.IO.InvalidDataException("The given instance specifies neither coordinates nor distances!"); if (data.Dimension > DistanceMatrixSizeLimit && (data.DistanceMeasure == DistanceMeasure.Att || data.DistanceMeasure == DistanceMeasure.Manhattan || data.DistanceMeasure == DistanceMeasure.Maximum)) throw new System.IO.InvalidDataException("The given instance uses an unsupported distance measure and is too large for using a distance matrix."); if (data.Coordinates != null && data.Coordinates.GetLength(1) != 2) throw new System.IO.InvalidDataException("The coordinates of the given instance are not in the right format, there need to be one row for each customer and two columns for the x and y coordinates."); Name = data.Name; Description = data.Description; ProbabilityMatrix = new DoubleArray(data.Probabilities); if (data.BestKnownTour != null) { BestKnownSolution = new Permutation(PermutationTypes.RelativeUndirected, data.BestKnownTour); } bool clearCoordinates = false, clearDistanceMatrix = false; if (data.Coordinates != null && data.Coordinates.GetLength(0) > 0) Coordinates = new DoubleMatrix(data.Coordinates); else clearCoordinates = true; // reset them after assigning the evaluator if (clearCoordinates) Coordinates = null; if (clearDistanceMatrix) DistanceMatrix = null; DistanceMatrix = new DistanceMatrix(data.GetDistanceMatrix()); Encoding.Length = data.Dimension; OnReset(); } } }