#region License Information
/* HeuristicLab
* Copyright (C) 2002-2015 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.Core;
using HeuristicLab.Optimization;
namespace HeuristicLab.Problems.Programmable {
public abstract class CompiledProblemDefinition : IProblemDefinition
where TEncoding : class, IEncoding
where TSolution : class, ISolution {
private TEncoding encoding;
public TEncoding Encoding {
get { return encoding; }
internal set {
if (value == null) throw new ArgumentNullException("The encoding must not be null.");
encoding = value;
}
}
public dynamic vars { get; set; }
public abstract void Initialize();
protected CompiledProblemDefinition() { }
protected CompiledProblemDefinition(TEncoding encoding)
: base() {
Encoding = encoding;
}
}
public abstract class CompiledSingleObjectiveProblemDefinition : CompiledProblemDefinition, ISingleObjectiveProblemDefinition
where TEncoding : class, IEncoding
where TSolution : class, ISolution {
protected CompiledSingleObjectiveProblemDefinition() : base() { }
protected CompiledSingleObjectiveProblemDefinition(TEncoding encoding)
: base(encoding) { }
#region ISingleObjectiveProblemDefinition Members
public abstract bool Maximization { get; }
public abstract double Evaluate(TSolution individual, IRandom random);
public abstract void Analyze(TSolution[] individuals, double[] qualities, ResultCollection results, IRandom random);
public abstract IEnumerable GetNeighbors(TSolution individual, IRandom random);
public bool IsBetter(double quality, double bestQuality) {
return Maximization ? quality > bestQuality : quality < bestQuality;
}
#endregion
}
public abstract class CompiledMultiObjectiveProblemDefinition : CompiledProblemDefinition, IMultiObjectiveProblemDefinition
where TEncoding : class, IEncoding
where TSolution : class, ISolution {
protected CompiledMultiObjectiveProblemDefinition() : base() { }
protected CompiledMultiObjectiveProblemDefinition(TEncoding encoding)
: base(encoding) { }
#region ISingleObjectiveProblemDefinition Members
public abstract bool[] Maximization { get; }
public abstract double[] Evaluate(TSolution individual, IRandom random);
public abstract void Analyze(TSolution[] individuals, double[][] qualities, ResultCollection results, IRandom random);
public abstract IEnumerable GetNeighbors(TSolution individual, IRandom random);
#endregion
}
}