#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 } }