#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);
}
}
}