#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.Linq; using HeuristicLab.Common; using HeuristicLab.Core; using HeuristicLab.Data; using HeuristicLab.Operators; using HeuristicLab.Optimization; using HeuristicLab.Parameters; using HeuristicLab.Persistence.Default.CompositeSerializers.Storable; using HeuristicLab.Problems.VehicleRouting.Interfaces; using HeuristicLab.Problems.VehicleRouting.ProblemInstances; using HeuristicLab.Problems.VehicleRouting.Variants; namespace HeuristicLab.Problems.VehicleRouting { /// /// An operator for analyzing the best solution of Vehicle Routing Problems. /// [Item("BestVRPSolutionAnalyzer", "An operator for analyzing the best solution of Vehicle Routing Problems.")] [StorableType("50979092-DCE8-49BD-BD04-44E53FB212C0")] public sealed class BestVRPSolutionAnalyzer : SingleSuccessorOperator, IAnalyzer, IGeneralVRPOperator, ISingleObjectiveOperator { public ILookupParameter ProblemInstanceParameter { get { return (ILookupParameter)Parameters["ProblemInstance"]; } } public ScopeTreeLookupParameter VRPToursParameter { get { return (ScopeTreeLookupParameter)Parameters["VRPTours"]; } } public ScopeTreeLookupParameter QualityParameter { get { return (ScopeTreeLookupParameter)Parameters["Quality"]; } } public ScopeTreeLookupParameter DistanceParameter { get { return (ScopeTreeLookupParameter)Parameters["Distance"]; } } public ScopeTreeLookupParameter VehiclesUtilizedParameter { get { return (ScopeTreeLookupParameter)Parameters["VehiclesUtilized"]; } } public LookupParameter BestSolutionParameter { get { return (LookupParameter)Parameters["BestSolution"]; } } public LookupParameter BestValidSolutionParameter { get { return (LookupParameter)Parameters["BestValidSolution"]; } } public ValueLookupParameter ResultsParameter { get { return (ValueLookupParameter)Parameters["Results"]; } } public LookupParameter BestKnownQualityParameter { get { return (LookupParameter)Parameters["BestKnownQuality"]; } } public LookupParameter BestKnownSolutionParameter { get { return (LookupParameter)Parameters["BestKnownSolution"]; } } public bool EnabledByDefault { get { return true; } } [StorableConstructor] private BestVRPSolutionAnalyzer(bool deserializing) : base(deserializing) { } public BestVRPSolutionAnalyzer() : base() { Parameters.Add(new LookupParameter("ProblemInstance", "The problem instance.")); Parameters.Add(new ScopeTreeLookupParameter("VRPTours", "The VRP tours which should be evaluated.")); Parameters.Add(new LookupParameter("BestKnownQuality", "The quality of the best known solution of this VRP instance.")); Parameters.Add(new LookupParameter("BestKnownSolution", "The best known solution of this VRP instance.")); Parameters.Add(new ScopeTreeLookupParameter("Quality", "The qualities of the VRP solutions which should be analyzed.")); Parameters.Add(new ScopeTreeLookupParameter("Distance", "The distances of the VRP solutions which should be analyzed.")); Parameters.Add(new ScopeTreeLookupParameter("VehiclesUtilized", "The utilized vehicles of the VRP solutions which should be analyzed.")); Parameters.Add(new LookupParameter("BestSolution", "The best VRP solution.")); Parameters.Add(new LookupParameter("BestValidSolution", "The best valid VRP solution.")); Parameters.Add(new ValueLookupParameter("Results", "The result collection where the best VRP solution should be stored.")); } public override IDeepCloneable Clone(Cloner cloner) { return new BestVRPSolutionAnalyzer(this, cloner); } private BestVRPSolutionAnalyzer(BestVRPSolutionAnalyzer original, Cloner cloner) : base(original, cloner) { } [StorableHook(HookType.AfterDeserialization)] private void AfterDeserialization() { #region Backwards Compatibility if (!Parameters.ContainsKey("BestKnownQuality")) { Parameters.Add(new LookupParameter("BestKnownQuality", "The quality of the best known solution of this VRP instance.")); } if (!Parameters.ContainsKey("BestKnownSolution")) { Parameters.Add(new LookupParameter("BestKnownSolution", "The best known solution of this VRP instance.")); } #endregion } public override IOperation Apply() { IVRPProblemInstance problemInstance = ProblemInstanceParameter.ActualValue; ItemArray solutions = VRPToursParameter.ActualValue; ResultCollection results = ResultsParameter.ActualValue; ItemArray qualities = QualityParameter.ActualValue; ItemArray distances = DistanceParameter.ActualValue; ItemArray vehiclesUtilizations = VehiclesUtilizedParameter.ActualValue; int i = qualities.Select((x, index) => new { index, x.Value }).OrderBy(x => x.Value).First().index; IVRPEncoding best = solutions[i].Clone() as IVRPEncoding; VRPSolution solution = BestSolutionParameter.ActualValue; if (solution == null) { solution = new VRPSolution(problemInstance, best.Clone() as IVRPEncoding, new DoubleValue(qualities[i].Value)); BestSolutionParameter.ActualValue = solution; results.Add(new Result("Best VRP Solution", solution)); results.Add(new Result("Best VRP Solution Distance", new DoubleValue(distances[i].Value))); results.Add(new Result("Best VRP Solution VehicleUtilization", new DoubleValue(vehiclesUtilizations[i].Value))); } else { VRPEvaluation eval = problemInstance.Evaluate(solution.Solution); if (qualities[i].Value <= eval.Quality) { solution.ProblemInstance = problemInstance; solution.Solution = best.Clone() as IVRPEncoding; solution.Quality.Value = qualities[i].Value; (results["Best VRP Solution Distance"].Value as DoubleValue).Value = distances[i].Value; (results["Best VRP Solution VehicleUtilization"].Value as DoubleValue).Value = vehiclesUtilizations[i].Value; } } var idx = qualities.Select((x, index) => new { index, x.Value }).Where(index => problemInstance.Feasible(solutions[index.index])).OrderBy(x => x.Value).FirstOrDefault(); if (idx != null) { int j = idx.index; IVRPEncoding bestFeasible = solutions[j].Clone() as IVRPEncoding; VRPSolution validSolution = BestValidSolutionParameter.ActualValue; if (validSolution == null) { validSolution = new VRPSolution(problemInstance, best.Clone() as IVRPEncoding, new DoubleValue(qualities[j].Value)); BestValidSolutionParameter.ActualValue = validSolution; if (results.ContainsKey("Best valid VRP Solution")) results["Best valid VRP Solution"].Value = validSolution; else results.Add(new Result("Best valid VRP Solution", validSolution)); results.Add(new Result("Best valid VRP Solution Distance", new DoubleValue(distances[j].Value))); results.Add(new Result("Best valid VRP Solution VehicleUtilization", new DoubleValue(vehiclesUtilizations[j].Value))); } else { if (qualities[j].Value <= validSolution.Quality.Value) { if (ProblemInstanceParameter.ActualValue.Feasible(best)) { validSolution.ProblemInstance = problemInstance; validSolution.Solution = best.Clone() as IVRPEncoding; validSolution.Quality.Value = qualities[j].Value; (results["Best valid VRP Solution Distance"].Value as DoubleValue).Value = distances[j].Value; (results["Best valid VRP Solution VehicleUtilization"].Value as DoubleValue).Value = vehiclesUtilizations[j].Value; } } } DoubleValue bestKnownQuality = BestKnownQualityParameter.ActualValue; if (bestKnownQuality == null || qualities[j].Value < bestKnownQuality.Value) { BestKnownQualityParameter.ActualValue = new DoubleValue(qualities[j].Value); BestKnownSolutionParameter.ActualValue = (VRPSolution)validSolution.Clone(); } } return base.Apply(); } } }