#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; using System.Threading; 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.PTSP { /// /// An operator that improves probabilistic traveling salesman solutions. /// /// /// The operator tries to improve the probabilistic traveling salesman solution by swapping two randomly chosen edges for a certain number of times. /// [Item("PTSP Estimated 2.5 Local Improvement", "An operator that improves probabilistic traveling salesman solutions. The operator tries to improve the probabilistic traveling salesman solution by swapping two randomly chosen edges for a certain number of times.")] [StorableType("8B04265A-50AD-4FAD-99F8-2357D6F10CC3")] public sealed class PTSPEstimatedTwoPointFiveLocalImprovement : SingleSuccessorOperator, IEstimatedPTSPOperator, ILocalImprovementOperator { public ILookupParameter LocalIterationsParameter { get { return (ILookupParameter)Parameters["LocalIterations"]; } } public IValueLookupParameter MaximumIterationsParameter { get { return (IValueLookupParameter)Parameters["MaximumIterations"]; } } public ILookupParameter EvaluatedSolutionsParameter { get { return (ILookupParameter)Parameters["EvaluatedSolutions"]; } } public ILookupParameter ResultsParameter { get { return (ILookupParameter)Parameters["Results"]; } } public ILookupParameter PermutationParameter { get { return (ILookupParameter)Parameters["Permutation"]; } } public ILookupParameter QualityParameter { get { return (ILookupParameter)Parameters["Quality"]; } } public ILookupParameter MaximizationParameter { get { return (ILookupParameter)Parameters["Maximization"]; } } public ILookupParameter DistanceMatrixParameter { get { return (ILookupParameter)Parameters["DistanceMatrix"]; } } public ILookupParameter> RealizationsParameter { get { return (ILookupParameter>)Parameters["Realizations"]; } } [StorableConstructor] private PTSPEstimatedTwoPointFiveLocalImprovement(StorableConstructorFlag _) : base(_) { } private PTSPEstimatedTwoPointFiveLocalImprovement(PTSPEstimatedTwoPointFiveLocalImprovement original, Cloner cloner) : base(original, cloner) { } public PTSPEstimatedTwoPointFiveLocalImprovement() : base() { Parameters.Add(new LookupParameter("Permutation", "The solution as permutation.")); Parameters.Add(new LookupParameter("LocalIterations", "The number of iterations that have already been performed.")); Parameters.Add(new ValueLookupParameter("MaximumIterations", "The maximum amount of iterations that should be performed (note that this operator will abort earlier when a local optimum is reached).", new IntValue(10000))); Parameters.Add(new LookupParameter("EvaluatedSolutions", "The amount of evaluated solutions (here a move is counted only as 4/n evaluated solutions with n being the length of the permutation).")); Parameters.Add(new LookupParameter("Results", "The collection where to store results.")); Parameters.Add(new LookupParameter("Quality", "The quality value of the assignment.")); Parameters.Add(new LookupParameter("Maximization", "True if the problem should be maximized or minimized.")); Parameters.Add(new LookupParameter("DistanceMatrix", "The matrix which contains the distances between the cities.")); Parameters.Add(new LookupParameter>("Realizations", "The list of samples drawn from all possible stochastic instances.")); } public override IDeepCloneable Clone(Cloner cloner) { return new PTSPEstimatedTwoPointFiveLocalImprovement(this, cloner); } public static void Improve(Permutation assignment, DoubleMatrix distances, DoubleValue quality, IntValue localIterations, IntValue evaluatedSolutions, bool maximization, int maxIterations, ItemList realizations, CancellationToken cancellation) { var distanceM = (DistanceMatrix)distances; Func distance = (a, b) => distanceM[a, b]; for (var i = localIterations.Value; i < maxIterations; i++) { TwoPointFiveMove bestMove = null; var bestQuality = 0.0; // we have to make an improvement, so 0 is the baseline var evaluations = 0.0; foreach (var move in ExhaustiveTwoPointFiveMoveGenerator.Generate(assignment)) { var moveQuality = PTSPEstimatedTwoPointFiveMoveEvaluator.EvaluateMove(assignment, move, distance, realizations); if (move.IsInvert) evaluations += realizations.Count * 4.0 / (assignment.Length * assignment.Length); else evaluations += realizations.Count * 6.0 / (assignment.Length * assignment.Length); if (maximization && moveQuality > bestQuality || !maximization && moveQuality < bestQuality) { bestQuality = moveQuality; bestMove = move; } } evaluatedSolutions.Value += (int)Math.Ceiling(evaluations); if (bestMove == null) break; TwoPointFiveMoveMaker.Apply(assignment, bestMove); quality.Value += bestQuality; localIterations.Value++; cancellation.ThrowIfCancellationRequested(); } } public override IOperation Apply() { var maxIterations = MaximumIterationsParameter.ActualValue.Value; var assignment = PermutationParameter.ActualValue; var maximization = MaximizationParameter.ActualValue.Value; var distances = DistanceMatrixParameter.ActualValue; var quality = QualityParameter.ActualValue; var localIterations = LocalIterationsParameter.ActualValue; var evaluations = EvaluatedSolutionsParameter.ActualValue; var realizations = RealizationsParameter.ActualValue; if (localIterations == null) { localIterations = new IntValue(0); LocalIterationsParameter.ActualValue = localIterations; } Improve(assignment, distances, quality, localIterations, evaluations, maximization, maxIterations, realizations, CancellationToken); localIterations.Value = 0; return base.Apply(); } } }