#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.Collections.Generic;
using System.Linq;
using System.Threading;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Encodings.IntegerVectorEncoding;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using HeuristicLab.Random;

namespace HeuristicLab.Problems.GeneralizedQuadraticAssignment {
  [Item("GreedyRandomizedSolutionCreator", "Creates a solution according to the procedure described in Mateus, G., Resende, M., and Silva, R. 2011. GRASP with path-relinking for the generalized quadratic assignment problem. Journal of Heuristics 17, Springer Netherlands, pp. 527-565.")]
  [StorableClass]
  public class GreedyRandomizedSolutionCreator : GQAPStochasticSolutionCreator {

    public IValueLookupParameter<IntValue> MaximumTriesParameter {
      get { return (IValueLookupParameter<IntValue>)Parameters["MaximumTries"]; }
    }
    public IValueLookupParameter<BoolValue> CreateMostFeasibleSolutionParameter {
      get { return (IValueLookupParameter<BoolValue>)Parameters["CreateMostFeasibleSolution"]; }
    }

    [StorableConstructor]
    protected GreedyRandomizedSolutionCreator(bool deserializing) : base(deserializing) { }
    protected GreedyRandomizedSolutionCreator(GreedyRandomizedSolutionCreator original, Cloner cloner)
      : base(original, cloner) { }
    public GreedyRandomizedSolutionCreator()
      : base() {
      Parameters.Add(new ValueLookupParameter<IntValue>("MaximumTries", "The maximum number of tries to create a feasible solution after which an exception is thrown. If it is set to 0 or a negative value there will be an infinite number of attempts.", new IntValue(100000)));
      Parameters.Add(new ValueLookupParameter<BoolValue>("CreateMostFeasibleSolution", "If this is set to true the operator will always succeed, and outputs the solution with the least violation instead of throwing an exception.", new BoolValue(false)));
    }

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

    public static IntegerVector CreateSolution(IRandom random, GQAPInstance problemInstance,
      int maximumTries, bool createMostFeasibleSolution, CancellationToken cancelToken) {
      var demands = problemInstance.Demands;
      var capacities = problemInstance.Capacities.ToArray();
      var equipments = demands.Length;
      var locations = capacities.Length;
      int tries = 0;
      var assignment = new int[equipments];
      var slack = new double[locations];
      double minViolation = double.MaxValue;
      int[] bestAssignment = null;
      var CF = new bool[equipments]; // set of chosen facilities / equipments
      var T = new List<int>(equipments); // set of facilities / equpiments that can be assigned to the set of chosen locations (CL)
      var CL_list = new List<int>(locations); // list of chosen locations
      var CL_selected = new bool[locations]; // bool decision if location is chosen
      var F = new List<int>(equipments); // set of (initially) all facilities / equipments
      var L = new List<int>(locations); // set of (initially) all locations
      
      while (maximumTries <= 0 || tries < maximumTries) {
        cancelToken.ThrowIfCancellationRequested();

        Array.Copy(capacities, slack, locations);
        Array.Clear(CF, 0, equipments);
        Array.Clear(CL_selected, 0, locations);
        CL_list.Clear();
        T.Clear();

        F.Clear(); F.AddRange(Enumerable.Range(0, equipments));
        L.Clear(); L.AddRange(Enumerable.Range(0, locations));

        double threshold = 1.0;
        do {
          if (L.Count > 0 && random.NextDouble() < threshold) {
            int l = L.SampleRandom(random);
            L.Remove(l);
            CL_list.Add(l);
            CL_selected[l] = true;
            T = new List<int>(WhereDemandEqualOrLess(F, GetMaximumSlack(slack, CL_selected), demands));
          }
          if (T.Count > 0) {
            var fidx = Enumerable.Range(0, T.Count).SampleRandom(random);
            var f = T[fidx];
            T.RemoveAt(fidx);
            F.Remove(f); // TODO: slow
            CF[f] = true;
            int l = WhereSlackGreaterOrEqual(CL_list, demands[f], slack).SampleRandom(random);
            assignment[f] = l + 1;
            slack[l] -= demands[f];
            T = new List<int>(WhereDemandEqualOrLess(F, GetMaximumSlack(slack, CL_selected), demands));
            threshold = 1.0 - (double)T.Count / Math.Max(F.Count, 1.0);
          }
        } while (T.Count > 0 || L.Count > 0);
        if (maximumTries > 0) tries++;
        if (F.Count == 0) {
          bestAssignment = assignment;
          break;
        } else if (createMostFeasibleSolution) {
          // complete the solution and remember the one with least violation
          foreach (var l in L.ToArray()) {
            CL_list.Add(l);
            CL_selected[l] = true;
            L.Remove(l);
          }
          while (F.Count > 0) {
            var f = F.Select((v, i) => new { Index = i, Value = v }).MaxItems(x => demands[x.Value]).SampleRandom(random);
            var l = CL_list.MaxItems(x => slack[x]).SampleRandom(random);
            F.RemoveAt(f.Index);
            assignment[f.Value] = l + 1;
            slack[l] -= demands[f.Value];
          }
          double violation = slack.Select(x => x < 0 ? -x : 0).Sum();
          if (violation < minViolation) {
            bestAssignment = assignment;
            assignment = new int[equipments];
            minViolation = violation;
          }
        }
      }

      if (bestAssignment == null || bestAssignment.Any(x => x == 0))
        throw new InvalidOperationException(String.Format("No solution could be found in {0} tries.", maximumTries));

      return new IntegerVector(bestAssignment.Select(x => x - 1).ToArray());
    }

    protected override IntegerVector CreateRandomSolution(IRandom random, GQAPInstance problemInstance) {
      return CreateSolution(random, problemInstance,
        MaximumTriesParameter.ActualValue.Value,
        CreateMostFeasibleSolutionParameter.ActualValue.Value,
        CancellationToken);
    }

    private static IEnumerable<int> WhereDemandEqualOrLess(IEnumerable<int> facilities, double maximum, DoubleArray demands) {
      foreach (int f in facilities) {
        if (demands[f] <= maximum) yield return f;
      }
    }

    private static double GetMaximumSlack(double[] slack, bool[] CL) {
      var max = double.MinValue;
      for (var i = 0; i < slack.Length; i++) {
        if (CL[i] && max < slack[i]) max = slack[i];
      }
      return max;
    }

    private static IEnumerable<int> WhereSlackGreaterOrEqual(IEnumerable<int> locations, double minimum, double[] slack) {
      foreach (int l in locations) {
        if (slack[l] >= minimum) yield return l;
      }
    }
  }
}