#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.Linq;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Operators;
using HeuristicLab.Optimization;
using HeuristicLab.Parameters;
using HEAL.Attic;
namespace HeuristicLab.Algorithms.RAPGA {
///
/// An operator that progressively selects offspring by adding it to a scope list.
///
///
/// The operator also performs duplication control.
///
[Item("ProgressiveOffspringPreserver", "An operator that progressively selects offspring by adding it to a scope list. The operator also performs duplication control.")]
[StorableType("36A99B15-7DF3-481A-8D76-24BF4ED7B6F8")]
public sealed class ProgressiveOffspringPreserver : SingleSuccessorOperator {
#region Parameter Properties
public ScopeParameter CurrentScopeParameter {
get { return (ScopeParameter)Parameters["CurrentScope"]; }
}
public ILookupParameter OffspringListParameter {
get { return (ILookupParameter)Parameters["OffspringList"]; }
}
public ILookupParameter ElitesParameter {
get { return (ILookupParameter)Parameters["Elites"]; }
}
public ILookupParameter MaximumPopulationSizeParameter {
get { return (ILookupParameter)Parameters["MaximumPopulationSize"]; }
}
public IValueLookupParameter SimilarityCalculatorParameter {
get { return (IValueLookupParameter)Parameters["SimilarityCalculator"]; }
}
#endregion
#region Properties
private IScope CurrentScope {
get { return CurrentScopeParameter.ActualValue; }
}
private ScopeList OffspringList {
get { return OffspringListParameter.ActualValue; }
}
private IntValue Elites {
get { return ElitesParameter.ActualValue; }
}
private IntValue MaximumPopulationSize {
get { return MaximumPopulationSizeParameter.ActualValue; }
}
#endregion
[StorableConstructor]
private ProgressiveOffspringPreserver(StorableConstructorFlag _) : base(_) { }
private ProgressiveOffspringPreserver(ProgressiveOffspringPreserver original, Cloner cloner) : base(original, cloner) { }
public ProgressiveOffspringPreserver()
: base() {
#region Create parameters
Parameters.Add(new ScopeParameter("CurrentScope", "The current scope that contains the offspring."));
Parameters.Add(new LookupParameter("OffspringList", "The list that contains the offspring."));
Parameters.Add(new LookupParameter("Elites", "The numer of elite solutions which are kept in each generation."));
Parameters.Add(new LookupParameter("MaximumPopulationSize", "The maximum size of the population of solutions."));
Parameters.Add(new ValueLookupParameter("SimilarityCalculator", "The similarity calculator that should be used to calculate solution similarity."));
#endregion
}
public override IDeepCloneable Clone(Cloner cloner) {
return new ProgressiveOffspringPreserver(this, cloner);
}
[StorableHook(HookType.AfterDeserialization)]
private void AfterDeserialization() {
// BackwardsCompatibility3.3
#region Backwards compatible code, remove with 3.4
if (!Parameters.ContainsKey("SimilarityCalculator"))
Parameters.Add(new ValueLookupParameter("SimilarityCalculator", "The similarity calculator that should be used to calculate solution similarity."));
#endregion
}
public override IOperation Apply() {
if (CurrentScope.SubScopes.Any()) { // offspring created
if (!OffspringList.Any()) OffspringList.AddRange(CurrentScope.SubScopes);
else { // stored offspring exists
var storedOffspringScope = new Scope();
storedOffspringScope.SubScopes.AddRange(OffspringList);
var similarityMatrix = SimilarityCalculatorParameter.ActualValue.CalculateSolutionCrowdSimilarity(CurrentScope, storedOffspringScope);
var createdOffspring = CurrentScope.SubScopes.ToArray();
int i = 0;
// as long as offspring is available and not enough offspring has been preserved
while (i < createdOffspring.Length && OffspringList.Count < MaximumPopulationSize.Value - Elites.Value) {
if (similarityMatrix[i].Any(x => x.IsAlmost(1.0))) createdOffspring[i] = null; // discard duplicates
else OffspringList.Add(createdOffspring[i]);
i++;
}
// discard remaining offspring
while (i < createdOffspring.Length) createdOffspring[i++] = null;
// clean current scope
CurrentScope.SubScopes.Replace(createdOffspring.Where(x => x != null));
}
}
return base.Apply();
}
}
}