#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 <http://www.gnu.org/licenses/>.
 */
#endregion

using System;
using System.Linq;
using HeuristicLab.Algorithms.CMAEvolutionStrategy;
using HeuristicLab.Algorithms.GeneticAlgorithm;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Encodings.RealVectorEncoding;
using HeuristicLab.Optimization;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using HeuristicLab.Problems.FacilityLocation;
using HeuristicLab.Problems.FacilityLocation.CplexSolver;
using HeuristicLab.Problems.VehicleRouting;
using HeuristicLab.Problems.VehicleRouting.Encodings.General;
using HeuristicLab.Selection;

namespace HeuristicLab.Networks.IntegratedOptimization.LocationRouting {
  [Item("LrpNetwork2", "Version 2 of a TTP optimization network.")]
  [Creatable("Optimization Networks")]
  [StorableClass]
  public sealed class LrpNetwork2 : LrpNetwork, IOptimizer {
    [StorableConstructor]
    private LrpNetwork2(bool deserializing) : base(deserializing) { }
    private LrpNetwork2(LrpNetwork2 original, Cloner cloner) : base(original, cloner) { }
    public LrpNetwork2() : this("LrpNetwork2") { }
    public LrpNetwork2(string name) : base(name) {
      Orchestrator = new LrpOrchestratorNode2(OrchestratorNodeName);
      MetaSolver = new OrchestratedAlgorithmNode(MetaSolverNodeName);
      FlpSolver = new OrchestratedAlgorithmNode(FlpSolverNodeName);
      VrpSolver = new OrchestratedAlgorithmNode(VrpSolverNodeName);

      var cmaes = new CMAEvolutionStrategy();
      var vp = new MinimizationVariegationProblem<RealVectorEncoding>();
      cmaes.Problem = vp;
      var cmaAnalyzer = cmaes.Analyzer.Operators.OfType<CMAAnalyzer>().Single();
      cmaes.Analyzer.Operators.SetItemCheckedState(cmaAnalyzer, true);
      cmaes.MaximumGenerations = 80;
      MetaSolver.Algorithm = cmaes;
      Orchestrator.MetaSolverOrchestrationPort.ConnectedPort = MetaSolver.OrchestrationPort;

      var cplexSolver = new FLPCplexSolver();
      cplexSolver.Problem = new FacilityLocationProblem();
      cplexSolver.MaximumRuntimeParameter.Value.Value = TimeSpan.FromSeconds(3.0);
      FlpSolver.Algorithm = cplexSolver;
      Orchestrator.FlpSolverOrchestrationPort.ConnectedPort = FlpSolver.OrchestrationPort;

      var ga = new GeneticAlgorithm();
      ga.Problem = new VehicleRoutingProblem();
      ga.PopulationSize.Value = 100;
      var crossover = ga.CrossoverParameter.ValidValues.OfType<MultiVRPSolutionCrossover>().Single(x => x.Name == "MultiVRPSolutionCrossover");
      ga.CrossoverParameter.Value = crossover;
      ga.MaximumGenerations.Value = 100;
      var mutator = ga.MutatorParameter.ValidValues.OfType<MultiVRPSolutionManipulator>().Single(x => x.Name == "MultiVRPSolutionManipulator");
      ga.MutatorParameter.Value = mutator;
      var selector = ga.SelectorParameter.ValidValues.OfType<TournamentSelector>().Single();
      ga.SelectorParameter.Value = selector;
      VrpSolver.Algorithm = ga;
      Orchestrator.VrpSolverOrchestrationPort.ConnectedPort = VrpSolver.OrchestrationPort;
    }

    public override IDeepCloneable Clone(Cloner cloner) {
      return new LrpNetwork2(this, cloner);
    }
  }
}