#region License Information
/* HeuristicLab
 * Copyright (C) 2002-2012 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.Collections.Generic;
using System.Linq;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Encodings.IntegerVectorEncoding;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using HeuristicLab.Problems.GeneralizedQuadraticAssignment.Common;

namespace HeuristicLab.Problems.GeneralizedQuadraticAssignment {

  [Item("DemandEquivalentSwapEquipmentManipluator", "Swaps equipment X from location A with as much equipments from location B that the demand of X is less than or equal to the demand of the swapped equipments in B.")]
  [StorableClass]
  public class DemandEquivalentSwapEquipmentManipluator : GQAPManipulator, IDemandsAwareGQAPOperator, ICapacitiesAwareGQAPOperator {

    public ILookupParameter<DoubleArray> DemandsParameter {
      get { return (ILookupParameter<DoubleArray>)Parameters["Demands"]; }
    }
    public ILookupParameter<DoubleArray> CapacitiesParameter {
      get { return (ILookupParameter<DoubleArray>)Parameters["Capacities"]; }
    }

    [StorableConstructor]
    protected DemandEquivalentSwapEquipmentManipluator(bool deserializing) : base(deserializing) { }
    protected DemandEquivalentSwapEquipmentManipluator(DemandEquivalentSwapEquipmentManipluator original, Cloner cloner) : base(original, cloner) { }
    public DemandEquivalentSwapEquipmentManipluator()
      : base() {
      Parameters.Add(new LookupParameter<DoubleArray>("Demands", GeneralizedQuadraticAssignmentProblem.DemandsDescription));
      Parameters.Add(new LookupParameter<DoubleArray>("Capacities", GeneralizedQuadraticAssignmentProblem.CapacitiesDescription));
    }

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

    public static void Apply(IRandom random, IntegerVector assignment, DoubleArray capacities, DoubleArray demands) {
      if (assignment.Length < 2) throw new InvalidOperationException("Vector is too small for swap operation.");
      int equipment1 = random.Next(assignment.Length), equipment2 = random.Next(assignment.Length);
      int counter = 1;
      while (assignment[equipment1] == assignment[equipment2] && counter < assignment.Length) {
        equipment2 = random.Next(assignment.Length);
        counter++;
      }
      if (assignment[equipment1] != assignment[equipment2]) {
        var groupedLocations = assignment
              .Select((value, index) => new { Index = index, Value = value })
              .GroupBy(x => x.Value)
              .ToDictionary(x => x.Key, y => new HashSet<int>(y.Select(x => x.Index)));
        double demand = demands[equipment1];
        int location1 = assignment[equipment1];
        int location2 = assignment[equipment2];

        assignment[equipment1] = location2;
        while (demand > 0) {
          demand -= demands[equipment2];
          assignment[equipment2] = location1;
          groupedLocations[location2].Remove(equipment2);
          if (!groupedLocations[location2].Any()) break;
          equipment2 = groupedLocations[location2].ChooseUniformRandom(random);
        }
      }
    }

    protected override void Manipulate(IRandom random, IntegerVector vector) {
      Apply(random, vector, CapacitiesParameter.ActualValue, DemandsParameter.ActualValue);
    }
  }
}