#region License Information
/* HeuristicLab
* Copyright (C) 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.Collections.Generic;
using System.Linq;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HEAL.Attic;
namespace HeuristicLab.Encodings.LinearLinkageEncoding {
[Item("Lowest Index First Crossover", "The Lowest Index First Crossover (LIFX) is implemented as described in Ülker, Ö., Özcan, E., Korkmaz, E. E. 2007. Linear linkage encoding in grouping problems: applications on graph coloring and timetabling. In Practice and Theory of Automated Timetabling VI, pp. 347-363. Springer Berlin Heidelberg.")]
[StorableType("1DFB1827-AFE6-4210-A542-F9EA112FF039")]
public sealed class LowestIndexFirstCrossover : LinearLinkageCrossover {
[StorableConstructor]
private LowestIndexFirstCrossover(StorableConstructorFlag _) : base(_) { }
private LowestIndexFirstCrossover(LowestIndexFirstCrossover original, Cloner cloner) : base(original, cloner) { }
public LowestIndexFirstCrossover() { }
public override IDeepCloneable Clone(Cloner cloner) {
return new LowestIndexFirstCrossover(this, cloner);
}
public static LinearLinkage Apply(IRandom random, ItemArray parents) {
var len = parents[0].Length;
var p = random.Next(parents.Length);
var child = LinearLinkage.SingleElementGroups(len);
var remaining = new SortedSet(Enumerable.Range(0, len));
do {
var i = remaining.Min;
foreach (var g in parents[p].GetGroupForward(i)) {
if (!remaining.Contains(g)) continue;
child[i] = g;
i = g;
remaining.Remove(g);
}
child[i] = i;
remaining.Remove(i);
p = (p + 1) % parents.Length;
} while (remaining.Count > 0);
return child;
}
protected override LinearLinkage Cross(IRandom random, ItemArray parents) {
return Apply(random, parents);
}
}
}