source: branches/Scheduling/HeuristicLab.Problems.Scheduling/3.3/Decoders/JSMDecoder.cs @ 8603

#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.Collections.Generic;
using System.Linq;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Encodings.PermutationEncoding;
using HeuristicLab.Encodings.ScheduleEncoding;
using HeuristicLab.Encodings.ScheduleEncoding.JobSequenceMatrix;
using HeuristicLab.Optimization;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;

namespace HeuristicLab.Problems.Scheduling {
  [Item("JobSequenceMatrixDecoder", "Applies the GifflerThompson algorithm to create an active schedule from a JobSequence Matrix.")]
  [StorableClass]
  public class JSMDecoder : ScheduleDecoder<JSMEncoding>, IStochasticOperator, IJSSPOperator {
    public ILookupParameter<IRandom> RandomParameter {
      get { return (LookupParameter<IRandom>)Parameters["Random"]; }
    }
    public ILookupParameter<ItemList<Job>> JobDataParameter {
      get { return (LookupParameter<ItemList<Job>>)Parameters["JobData"]; }
    }

    #region Private Members
    [Storable]
    private Schedule resultingSchedule;

    [Storable]
    private ItemList<Job> jobs;

    [Storable]
    private JSMDecodingErrorPolicyTypes decodingErrorPolicy = JSMDecodingErrorPolicyTypes.GuidedPolicy;

    [Storable]
    private JSMForcingStrategyTypes forcingStrategy = JSMForcingStrategyTypes.ShiftForcing;
    #endregion

    [StorableConstructor]
    protected JSMDecoder(bool deserializing) : base(deserializing) { }
    protected JSMDecoder(JSMDecoder original, Cloner cloner)
      : base(original, cloner) {
      this.resultingSchedule = cloner.Clone(original.resultingSchedule);
      this.jobs = cloner.Clone(original.jobs);
      this.decodingErrorPolicy = original.decodingErrorPolicy;
      this.forcingStrategy = original.forcingStrategy;
    }
    public override IDeepCloneable Clone(Cloner cloner) {
      return new JSMDecoder(this, cloner);
    }

    public JSMDecoder()
      : base() {
      Parameters.Add(new LookupParameter<IRandom>("Random", "The pseudo random number generator which should be used for stochastic manipulation operators."));
      Parameters.Add(new LookupParameter<ItemList<Job>>("JobData", "Job data taken from the Schedulingproblem - Instance."));
      ScheduleEncodingParameter.ActualName = "JobSequenceMatrix";
    }


    private Task SelectTaskFromConflictSet(int conflictedResourceNr, int progressOnConflictedResource, ItemList<Task> conflictSet, ItemList<Permutation> jsm) {
      if (conflictSet.Count == 1)
        return conflictSet[0];

      //get solutionCandidate from jobSequencingMatrix
      int solutionCandidateJobNr = jsm[conflictedResourceNr][progressOnConflictedResource];

      //scan conflictSet for given solutionCandidate, and return if found
      foreach (Task t in conflictSet) {
        if (t.JobNr == solutionCandidateJobNr)
          return t;
      }

      //if solutionCandidate wasn't found in conflictSet apply DecodingErrorPolicy and ForcingPolicy
      Task result = ApplyDecodingErrorPolicy(conflictSet, jsm[conflictedResourceNr], progressOnConflictedResource);
      int newResolutionIndex = 0;

      while (newResolutionIndex < jsm[conflictedResourceNr].Length && jsm[conflictedResourceNr][newResolutionIndex] != result.JobNr)
        newResolutionIndex++;
      ApplyForcingStrategy(jsm, conflictedResourceNr, newResolutionIndex, progressOnConflictedResource, result.JobNr);

      return result;
    }
    private Task ApplyDecodingErrorPolicy(ItemList<Task> conflictSet, Permutation resource, int progress) {
      if (decodingErrorPolicy == JSMDecodingErrorPolicyTypes.RandomPolicy) {
        //Random
        return conflictSet[RandomParameter.ActualValue.Next(conflictSet.Count - 1)];
      } else {
        //Guided
        for (int i = progress; i < resource.Length; i++) {
          int j = 0;
          while (j < conflictSet.Count && conflictSet[j].JobNr != resource[i])
            j++;

          if (j < conflictSet.Count)
            return (conflictSet[j]);
        }
        return conflictSet[RandomParameter.ActualValue.Next(conflictSet.Count - 1)];
      }
    }
    private void ApplyForcingStrategy(ItemList<Permutation> jsm, int conflictedResource, int newResolutionIndex, int progressOnResource, int newResolution) {
      if (forcingStrategy == JSMForcingStrategyTypes.SwapForcing) {
        //SwapForcing
        jsm[conflictedResource][newResolutionIndex] = jsm[conflictedResource][progressOnResource];
        jsm[conflictedResource][progressOnResource] = newResolution;
      } else {
        //ShiftForcing
        List<int> asList = jsm[conflictedResource].ToList<int>();
        if (newResolutionIndex > progressOnResource) {
          asList.RemoveAt(newResolutionIndex);
          asList.Insert(progressOnResource, newResolution);
        } else {
          asList.Insert(progressOnResource, newResolution);
          asList.RemoveAt(newResolutionIndex);
        }
        jsm[conflictedResource] = new Permutation(PermutationTypes.Absolute, asList.ToArray<int>());
      }
    }

    public Schedule CreateScheduleFromEncoding(JSMEncoding solution, ItemList<Job> jobData) {
      ItemList<Permutation> jobSequenceMatrix = solution.JobSequenceMatrix;

      jobs = (ItemList<Job>)jobData.Clone();
      resultingSchedule = new Schedule(jobs[0].Tasks.Count);

      //Reset scheduled tasks in result
      foreach (Job j in jobs) {
        foreach (Task t in j.Tasks) {
          t.IsScheduled = false;
        }
      }

      //GT-Algorithm
      //STEP 0 - Compute a list of "earliest operations"
      ItemList<Task> earliestTasksList = GTAlgorithmUtils.GetEarliestNotScheduledTasks(jobs);
      while (earliestTasksList.Count > 0) {
        //STEP 1 - Get earliest not scheduled operation with minimal earliest completing time
        Task minimal = GTAlgorithmUtils.GetTaskWithMinimalEC(earliestTasksList, resultingSchedule);
        int conflictedResourceNr = minimal.ResourceNr;
        Resource conflictedResource = resultingSchedule.Resources[conflictedResourceNr];

        //STEP 2 - Compute a conflict set of all operations that can be scheduled on the conflicted resource
        ItemList<Task> conflictSet = GTAlgorithmUtils.GetConflictSetForTask(minimal, earliestTasksList, jobs, resultingSchedule);

        //STEP 3 - Select a task from the conflict set
        int progressOnResource = conflictedResource.Tasks.Count;
        Task selectedTask = SelectTaskFromConflictSet(conflictedResourceNr, progressOnResource, conflictSet, jobSequenceMatrix);

        //STEP 4 - Add the selected task to the current schedule 
        selectedTask.IsScheduled = true;
        double startTime = GTAlgorithmUtils.ComputeEarliestStartTime(selectedTask, resultingSchedule);
        resultingSchedule.ScheduleTask(selectedTask.ResourceNr, startTime, selectedTask.Duration, selectedTask.JobNr);

        //STEP 5 - Back to STEP 1
        earliestTasksList = GTAlgorithmUtils.GetEarliestNotScheduledTasks(jobs);
      }

      return resultingSchedule;
    }

    public override Schedule CreateScheduleFromEncoding(JSMEncoding solution) {
      return CreateScheduleFromEncoding(solution, JobDataParameter.ActualValue);
    }

    public override IOperation Apply() {
      return base.Apply();
    }
  }
}