#region License Information /* HeuristicLab * Copyright (C) 2002-2019 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.Linq; using HeuristicLab.Common; using HeuristicLab.Core; using HeuristicLab.Data; using HeuristicLab.Encodings.PermutationEncoding; using HeuristicLab.Operators; using HeuristicLab.Optimization; using HeuristicLab.Parameters; using HEAL.Attic; namespace HeuristicLab.Problems.TravelingSalesman { /// /// An operator for analyzing the best solution of Traveling Salesman Problems given in path representation using city coordinates. /// [Item("BestTSPSolutionAnalyzer", "An operator for analyzing the best solution of Traveling Salesman Problems given in path representation using city coordinates.")] [StorableType("86D3A4A2-C91C-46D4-9644-10F88F94FEA1")] public sealed class BestTSPSolutionAnalyzer : SingleSuccessorOperator, IAnalyzer, ISingleObjectiveOperator { public bool EnabledByDefault { get { return true; } } public LookupParameter MaximizationParameter { get { return (LookupParameter)Parameters["Maximization"]; } } public LookupParameter CoordinatesParameter { get { return (LookupParameter)Parameters["Coordinates"]; } } public ScopeTreeLookupParameter PermutationParameter { get { return (ScopeTreeLookupParameter)Parameters["Permutation"]; } } public ScopeTreeLookupParameter QualityParameter { get { return (ScopeTreeLookupParameter)Parameters["Quality"]; } } public LookupParameter BestSolutionParameter { get { return (LookupParameter)Parameters["BestSolution"]; } } public ValueLookupParameter ResultsParameter { get { return (ValueLookupParameter)Parameters["Results"]; } } public LookupParameter BestKnownQualityParameter { get { return (LookupParameter)Parameters["BestKnownQuality"]; } } public LookupParameter BestKnownSolutionParameter { get { return (LookupParameter)Parameters["BestKnownSolution"]; } } [StorableConstructor] private BestTSPSolutionAnalyzer(StorableConstructorFlag _) : base(_) { } private BestTSPSolutionAnalyzer(BestTSPSolutionAnalyzer original, Cloner cloner) : base(original, cloner) { } public override IDeepCloneable Clone(Cloner cloner) { return new BestTSPSolutionAnalyzer(this, cloner); } public BestTSPSolutionAnalyzer() : base() { Parameters.Add(new LookupParameter("Maximization", "True if the problem is a maximization problem.")); Parameters.Add(new LookupParameter("Coordinates", "The x- and y-Coordinates of the cities.")); Parameters.Add(new ScopeTreeLookupParameter("Permutation", "The TSP solutions given in path representation from which the best solution should be analyzed.")); Parameters.Add(new ScopeTreeLookupParameter("Quality", "The qualities of the TSP solutions which should be analyzed.")); Parameters.Add(new LookupParameter("BestSolution", "The best TSP solution.")); Parameters.Add(new ValueLookupParameter("Results", "The result collection where the best TSP solution should be stored.")); Parameters.Add(new LookupParameter("BestKnownQuality", "The quality of the best known solution of this TSP instance.")); Parameters.Add(new LookupParameter("BestKnownSolution", "The best known solution of this TSP instance.")); MaximizationParameter.Hidden = true; CoordinatesParameter.Hidden = true; PermutationParameter.Hidden = true; QualityParameter.Hidden = true; BestSolutionParameter.Hidden = true; ResultsParameter.Hidden = true; BestKnownQualityParameter.Hidden = true; BestKnownSolutionParameter.Hidden = true; } public override IOperation Apply() { DoubleMatrix coordinates = CoordinatesParameter.ActualValue; ItemArray permutations = PermutationParameter.ActualValue; ItemArray qualities = QualityParameter.ActualValue; ResultCollection results = ResultsParameter.ActualValue; bool max = MaximizationParameter.ActualValue.Value; DoubleValue bestKnownQuality = BestKnownQualityParameter.ActualValue; int i = -1; if (!max) i = qualities.Select((x, index) => new { index, x.Value }).OrderBy(x => x.Value).First().index; else i = qualities.Select((x, index) => new { index, x.Value }).OrderByDescending(x => x.Value).First().index; if (bestKnownQuality == null || max && qualities[i].Value > bestKnownQuality.Value || !max && qualities[i].Value < bestKnownQuality.Value) { BestKnownQualityParameter.ActualValue = new DoubleValue(qualities[i].Value); BestKnownSolutionParameter.ActualValue = (Permutation)permutations[i].Clone(); } PathTSPTour tour = BestSolutionParameter.ActualValue; if (tour == null) { tour = new PathTSPTour(coordinates, (Permutation)permutations[i].Clone(), new DoubleValue(qualities[i].Value)); BestSolutionParameter.ActualValue = tour; results.Add(new Result("Best TSP Solution", tour)); } else { if (max && tour.Quality.Value < qualities[i].Value || !max && tour.Quality.Value > qualities[i].Value) { tour.Coordinates = coordinates; tour.Permutation = (Permutation)permutations[i].Clone(); tour.Quality.Value = qualities[i].Value; } } return base.Apply(); } } }