#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();
}
}
}