#region License Information /* HeuristicLab * Copyright (C) 2002-2018 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 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.Variants; namespace HeuristicLab.Problems.VehicleRouting { /// /// An operator for adaptive constraint relaxation. /// [Item("TimeWindowRelaxationVRPAnalyzer", "An operator for adaptively relaxing the time window constraints.")] [StorableClass] public class TimeWindowRelaxationVRPAnalyzer : SingleSuccessorOperator, IAnalyzer, ITimeWindowedOperator, 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 TardinessParameter { get { return (ScopeTreeLookupParameter)Parameters["Tardiness"]; } } public IValueParameter SigmaParameter { get { return (IValueParameter)Parameters["Sigma"]; } } public IValueParameter PhiParameter { get { return (IValueParameter)Parameters["Phi"]; } } public IValueParameter MinPenaltyFactorParameter { get { return (IValueParameter)Parameters["MinPenaltyFactor"]; } } public IValueParameter MaxPenaltyFactorParameter { get { return (IValueParameter)Parameters["MaxPenaltyFactor"]; } } public ValueLookupParameter ResultsParameter { get { return (ValueLookupParameter)Parameters["Results"]; } } public bool EnabledByDefault { get { return false; } } [StorableConstructor] protected TimeWindowRelaxationVRPAnalyzer(bool deserializing) : base(deserializing) { } public TimeWindowRelaxationVRPAnalyzer() : base() { Parameters.Add(new LookupParameter("ProblemInstance", "The problem instance.")); Parameters.Add(new ScopeTreeLookupParameter("VRPTours", "The VRP tours which should be evaluated.")); Parameters.Add(new ScopeTreeLookupParameter("Quality", "The qualities of the VRP solutions which should be analyzed.")); Parameters.Add(new ScopeTreeLookupParameter("Tardiness", "The tardiness of the VRP solutions which should be analyzed.")); Parameters.Add(new ValueParameter("Sigma", "The sigma applied to the penalty factor.", new DoubleValue(0.5))); Parameters.Add(new ValueParameter("Phi", "The phi applied to the penalty factor.", new DoubleValue(0.5))); Parameters.Add(new ValueParameter("MinPenaltyFactor", "The minimum penalty factor.", new DoubleValue(0.01))); Parameters.Add(new ValueParameter("MaxPenaltyFactor", "The maximum penalty factor.", new DoubleValue(100000))); Parameters.Add(new ValueLookupParameter("Results", "The result collection where the best VRP solution should be stored.")); } public override IDeepCloneable Clone(Cloner cloner) { return new TimeWindowRelaxationVRPAnalyzer(this, cloner); } protected TimeWindowRelaxationVRPAnalyzer(TimeWindowRelaxationVRPAnalyzer original, Cloner cloner) : base(original, cloner) { } [StorableHook(HookType.AfterDeserialization)] private void AfterDeserialization() { // BackwardsCompatibility3.3 #region Backwards compatible code, remove with 3.4 if (!Parameters.ContainsKey("MaxPenaltyFactor")) { Parameters.Add(new ValueParameter("MaxPenaltyFactor", "The maximum penalty factor.", new DoubleValue(100000))); } #endregion } public override IOperation Apply() { ITimeWindowedProblemInstance vrptw = ProblemInstanceParameter.ActualValue as ITimeWindowedProblemInstance; ResultCollection results = ResultsParameter.ActualValue; ItemArray qualities = QualityParameter.ActualValue; ItemArray tardiness = TardinessParameter.ActualValue; double sigma = SigmaParameter.Value.Value; double phi = PhiParameter.Value.Value; double minPenalty = MinPenaltyFactorParameter.Value.Value; double maxPenalty = MaxPenaltyFactorParameter.Value.Value; for (int j = 0; j < qualities.Length; j++) { qualities[j].Value -= tardiness[j].Value * vrptw.TardinessPenalty.Value; } int validCount = 0; for (int j = 0; j < qualities.Length; j++) { if (tardiness[j].Value == 0) validCount++; } double factor = 1.0 - ((double)validCount / (double)qualities.Length); double min = vrptw.TardinessPenalty.Value / (1 + sigma); double max = vrptw.TardinessPenalty.Value * (1 + phi); vrptw.CurrentTardinessPenalty = new DoubleValue(min + (max - min) * factor); if (vrptw.CurrentTardinessPenalty.Value < minPenalty) vrptw.CurrentTardinessPenalty.Value = minPenalty; if (vrptw.CurrentTardinessPenalty.Value > maxPenalty) vrptw.CurrentTardinessPenalty.Value = maxPenalty; for (int j = 0; j < qualities.Length; j++) { qualities[j].Value += tardiness[j].Value * vrptw.CurrentTardinessPenalty.Value; } if (!results.ContainsKey("Current Tardiness Penalty")) { results.Add(new Result("Current Tardiness Penalty", new DoubleValue(vrptw.CurrentTardinessPenalty.Value))); } else { (results["Current Tardiness Penalty"].Value as DoubleValue).Value = vrptw.CurrentTardinessPenalty.Value; } return base.Apply(); } } }