#region License Information /* HeuristicLab * Copyright (C) 2002-2016 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 System.Globalization; using System.Linq; using HeuristicLab.Common; using HeuristicLab.Core; using HeuristicLab.Data; using HeuristicLab.Operators; using HeuristicLab.Parameters; using HeuristicLab.Persistence.Default.CompositeSerializers.Storable; namespace HeuristicLab.Optimization { [Item("Single-objective MoveGenerator", "Calls the GetNeighbors method of the problem definition to obtain the moves.")] [StorableClass] public class SingleObjectiveMoveGenerator : SingleSuccessorOperator, INeighborBasedOperator, IMultiMoveGenerator, IStochasticOperator, ISingleObjectiveMoveOperator { public ILookupParameter RandomParameter { get { return (ILookupParameter)Parameters["Random"]; } } public IValueLookupParameter SampleSizeParameter { get { return (IValueLookupParameter)Parameters["SampleSize"]; } } public ILookupParameter EncodingParameter { get { return (ILookupParameter)Parameters["Encoding"]; } } public Func> GetNeighborsFunc { get; set; } [StorableConstructor] protected SingleObjectiveMoveGenerator(bool deserializing) : base(deserializing) { } protected SingleObjectiveMoveGenerator(SingleObjectiveMoveGenerator original, Cloner cloner) : base(original, cloner) { } public SingleObjectiveMoveGenerator() { Parameters.Add(new LookupParameter("Random", "The random number generator to use.")); Parameters.Add(new ValueLookupParameter("SampleSize", "The number of moves to sample.")); Parameters.Add(new LookupParameter("Encoding", "An item that holds the problem's encoding.")); } public override IDeepCloneable Clone(Cloner cloner) { return new SingleObjectiveMoveGenerator(this, cloner); } public override IOperation Apply() { var random = RandomParameter.ActualValue; var sampleSize = SampleSizeParameter.ActualValue.Value; var encoding = EncodingParameter.ActualValue; var individual = encoding.GetIndividual(ExecutionContext.Scope); var nbhood = GetNeighborsFunc(individual, random).Take(sampleSize).ToList(); var moveScopes = new Scope[nbhood.Count]; for (int i = 0; i < moveScopes.Length; i++) { moveScopes[i] = new Scope(i.ToString(CultureInfo.InvariantCulture.NumberFormat)); nbhood[i].CopyToScope(moveScopes[i]); } ExecutionContext.Scope.SubScopes.AddRange(moveScopes); return base.Apply(); } } }