#region License Information /* HeuristicLab * Copyright (C) 2002-2017 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.Linq; using System.Threading; using HEAL.Attic; using HeuristicLab.Common; using HeuristicLab.Core; using HeuristicLab.Data; using HeuristicLab.Encodings.IntegerVectorEncoding; using HeuristicLab.Optimization; using HeuristicLab.Parameters; namespace HeuristicLab.Problems.GeneralizedQuadraticAssignment.Algorithms.LAHC { [Item("LAHC (GQAP)", "Late-acceptance hill climber for the GQAP.")] [Creatable(CreatableAttribute.Categories.SingleSolutionAlgorithms)] [StorableType("41FABEE1-506A-45FE-A6D3-57932036AEC8")] public sealed class LAHC : StochasticAlgorithm { public override bool SupportsPause { get { return true; } } public override Type ProblemType { get { return typeof(GQAP); } } public new GQAP Problem { get { return (GQAP)base.Problem; } set { base.Problem = value; } } [Storable] private FixedValueParameter memorySizeParameter; public IFixedValueParameter MemorySizeParameter { get { return memorySizeParameter; } } public int MemorySize { get { return memorySizeParameter.Value.Value; } set { memorySizeParameter.Value.Value = value; } } [StorableConstructor] private LAHC(StorableConstructorFlag _) : base(_) { } private LAHC(LAHC original, Cloner cloner) : base(original, cloner) { memorySizeParameter = cloner.Clone(original.memorySizeParameter); } public LAHC() { Parameters.Add(memorySizeParameter = new FixedValueParameter("MemorySize", "The size of the memory, the shorter the more greedy LAHC performs.", new IntValue(100))); Problem = new GQAP(); } public override IDeepCloneable Clone(Cloner cloner) { return new LAHC(this, cloner); } protected override void Initialize(CancellationToken token) { base.Initialize(token); Context.Problem = Problem; Context.LastSuccess = 0; var assign = new IntegerVector(Problem.ProblemInstance.Demands.Length, Context.Random, 0, Problem.ProblemInstance.Capacities.Length); var eval = Problem.ProblemInstance.Evaluate(assign); var fit = Problem.ProblemInstance.ToSingleObjective(eval); Context.EvaluatedSolutions++; var candidate = new GQAPSolution(assign, eval); Context.ReplaceIncumbent(Context.ToScope(candidate, fit)); Context.BestQuality = fit; Context.BestSolution = (GQAPSolution)candidate.Clone(); Context.Memory = new DoubleArray(Enumerable.Repeat(Context.BestQuality, MemorySize).ToArray()); Results.Add(new Result("Iterations", new IntValue(Context.Iterations))); Results.Add(new Result("EvaluatedSolutions", new IntValue(Context.EvaluatedSolutions))); Results.Add(new Result("BestQuality", new DoubleValue(Context.BestQuality))); Results.Add(new Result("BestSolution", Context.BestSolution)); try { Context.RunOperator(Analyzer, token); } catch (OperationCanceledException) { } } protected override void Run(CancellationToken cancellationToken) { base.Run(cancellationToken); var lastUpdate = ExecutionTime; while (!StoppingCriterion()) { var move = StochasticNMoveSingleMoveGenerator.GenerateOneMove(Context.Random, Context.Incumbent.Solution.Assignment, Problem.ProblemInstance.Capacities); var moveEval = GQAPNMoveEvaluator.Evaluate(move, Context.Incumbent.Solution.Assignment, Context.Incumbent.Solution.Evaluation, Problem.ProblemInstance); if (Context.Iterations % Problem.ProblemInstance.Demands.Length == 0) Context.EvaluatedSolutions++; var nextFit = Problem.ProblemInstance.ToSingleObjective(moveEval); var nextVec = new IntegerVector(Context.Incumbent.Solution.Assignment); NMoveMaker.Apply(nextVec, move); var v = Context.Iterations % Context.Memory.Length; Context.Iterations++; var prevFit = Context.Memory[v]; var accept = nextFit <= Context.Incumbent.Fitness || nextFit <= prevFit; if (accept && nextFit < Context.Incumbent.Fitness) Context.LastSuccess = Context.Iterations; if (accept) { Context.ReplaceIncumbent(Context.ToScope(new GQAPSolution(nextVec, moveEval), nextFit)); if (nextFit < Context.BestQuality) { Context.BestSolution = (GQAPSolution)Context.Incumbent.Solution.Clone(); Context.BestQuality = nextFit; } } if (Context.Incumbent.Fitness < prevFit) Context.Memory[v] = Context.Incumbent.Fitness; IResult result; if (ExecutionTime - lastUpdate > TimeSpan.FromSeconds(1)) { if (Results.TryGetValue("Iterations", out result)) ((IntValue)result.Value).Value = Context.Iterations; else Results.Add(new Result("Iterations", new IntValue(Context.Iterations))); if (Results.TryGetValue("EvaluatedSolutions", out result)) ((IntValue)result.Value).Value = Context.EvaluatedSolutions; else Results.Add(new Result("EvaluatedSolutions", new IntValue(Context.EvaluatedSolutions))); lastUpdate = ExecutionTime; } if (Results.TryGetValue("BestQuality", out result)) ((DoubleValue)result.Value).Value = Context.BestQuality; else Results.Add(new Result("BestQuality", new DoubleValue(Context.BestQuality))); if (Results.TryGetValue("BestSolution", out result)) result.Value = Context.BestSolution; else Results.Add(new Result("BestSolution", Context.BestSolution)); try { Context.RunOperator(Analyzer, cancellationToken); } catch (OperationCanceledException) { } if (cancellationToken.IsCancellationRequested) break; } IResult result2; if (Results.TryGetValue("Iterations", out result2)) ((IntValue)result2.Value).Value = Context.Iterations; else Results.Add(new Result("Iterations", new IntValue(Context.Iterations))); if (Results.TryGetValue("EvaluatedSolutions", out result2)) ((IntValue)result2.Value).Value = Context.EvaluatedSolutions; else Results.Add(new Result("EvaluatedSolutions", new IntValue(Context.EvaluatedSolutions))); } } }