#region License Information
/* HeuristicLab
* Copyright (C) 2002-2019 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
* and the BEACON Center for the Study of Evolution in Action.
*
* 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 HeuristicLab.Encodings.BinaryVectorEncoding;
using HEAL.Attic;
namespace HeuristicLab.Algorithms.ParameterlessPopulationPyramid {
// This code is based off the publication
// B. W. Goldman and W. F. Punch, "Parameter-less Population Pyramid," GECCO, pp. 785–792, 2014
// and the original source code in C++11 available from: https://github.com/brianwgoldman/Parameter-less_Population_Pyramid
[StorableType("E09EB41C-B95C-40DF-BF60-8F1E21E9892F")]
public class Population : DeepCloneable {
[Storable]
public List Solutions {
get;
private set;
}
[Storable]
public LinkageTree Tree {
get;
private set;
}
[StorableConstructor]
protected Population(StorableConstructorFlag _) { }
protected Population(Population original, Cloner cloner) : base(original, cloner) {
Solutions = original.Solutions.Select(cloner.Clone).ToList();
Tree = cloner.Clone(original.Tree);
}
public override IDeepCloneable Clone(Cloner cloner) {
return new Population(this, cloner);
}
public Population(int length, IRandom rand) {
Solutions = new List();
Tree = new LinkageTree(length, rand);
}
public void Add(BinaryVector solution) {
Solutions.Add(solution);
Tree.Add(solution);
}
}
}