#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.Collections.Generic; using HeuristicLab.Common; using HeuristicLab.Core; using HeuristicLab.Data; using HeuristicLab.Optimization; using HeuristicLab.Parameters; using HEAL.Attic; namespace HeuristicLab.Encodings.PermutationEncoding { [Item("StochasticInsertionMultiMoveGenerator", "Generates all possible insertion moves (3-opt) from a few numbers in a given permutation.")] [StorableType("27AFEE18-D94C-467C-AB45-F81ABB879B16")] public class StochasticInsertionMultiMoveGenerator : TranslocationMoveGenerator, IMultiMoveGenerator, IStochasticOperator { public ILookupParameter RandomParameter { get { return (ILookupParameter)Parameters["Random"]; } } public IValueLookupParameter SampleSizeParameter { get { return (IValueLookupParameter)Parameters["SampleSize"]; } } public IntValue SampleSize { get { return SampleSizeParameter.Value; } set { SampleSizeParameter.Value = value; } } [StorableConstructor] protected StochasticInsertionMultiMoveGenerator(StorableConstructorFlag _) : base(_) { } protected StochasticInsertionMultiMoveGenerator(StochasticInsertionMultiMoveGenerator original, Cloner cloner) : base(original, cloner) { } public StochasticInsertionMultiMoveGenerator() : base() { Parameters.Add(new LookupParameter("Random", "The random number generator to use.")); Parameters.Add(new ValueLookupParameter("SampleSize", "The number of moves to generate.")); } public override IDeepCloneable Clone(Cloner cloner) { return new StochasticInsertionMultiMoveGenerator(this, cloner); } public static TranslocationMove[] Apply(Permutation permutation, IRandom random, int sampleSize) { int length = permutation.Length; if (length == 1) throw new ArgumentException("ExhaustiveSingleInsertionMoveGenerator: There cannot be an insertion move given a permutation of length 1.", "permutation"); TranslocationMove[] moves = new TranslocationMove[sampleSize]; int count = 0; HashSet usedIndices = new HashSet(); while (count < sampleSize) { int index = random.Next(length); if (usedIndices.Count != length) while (usedIndices.Contains(index)) index = random.Next(length); usedIndices.Add(index); if (permutation.PermutationType == PermutationTypes.Absolute) { for (int j = 1; j <= length - 1; j++) { moves[count++] = new TranslocationMove(index, index, (index + j) % length); if (count == sampleSize) break; } } else { if (length > 2) { for (int j = 1; j < length - 1; j++) { int insertPoint = (index + j) % length; if (index + j >= length) insertPoint++; moves[count++] = new TranslocationMove(index, index, insertPoint); if (count == sampleSize) break; } } else { // doesn't make sense, but just create a dummy move to not crash the algorithms moves = new TranslocationMove[1]; moves[0] = new TranslocationMove(0, 0, 1); count = sampleSize; } } } return moves; } protected override TranslocationMove[] GenerateMoves(Permutation permutation) { IRandom random = RandomParameter.ActualValue; if (random == null) throw new InvalidOperationException(Name + ": No random number generator found."); return Apply(permutation, random, SampleSizeParameter.ActualValue.Value); } } }