#region License Information
/* HeuristicLab
* Copyright (C) 2002-2019 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 HEAL.Fossil;
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.")]
[StorableType("2CF57A00-547B-46E8-8B55-D626EB2D61DD")]
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(StorableConstructorFlag _) : base(_) { }
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();
}
}
}