source: branches/1614_GeneralizedQAP/HeuristicLab.Problems.GeneralizedQuadraticAssignment.Algorithms/3.3/CPLEX/GQAP-FY.cs @ 16375

#region License Information
/* HeuristicLab
 * Copyright (C) 2002-2017 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
 *
 * This file is part of HeuristicLab.
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 * HeuristicLab is free software: you can redistribute it and/or modify
 * it under the terms of the GNU General Public License as published by
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 * GNU General Public License for more details.
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 * You should have received a copy of the GNU General Public License
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 */
#endregion

using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using ILOG.CPLEX;
using ILOG.OPL;

namespace HeuristicLab.Problems.GeneralizedQuadraticAssignment.Algorithms.CPLEX {
  [Item("FY-Linearization CPLEX (GQAP)", "")]
  [StorableClass]
  [Creatable(CreatableAttribute.Categories.Algorithms)]
  public sealed class GQAP_FY : CplexSolver {
    
    [StorableConstructor]
    private GQAP_FY(bool deserializing) : base(deserializing) { }
    private GQAP_FY(GQAP_FY original, Cloner cloner)
    : base(original, cloner) {
    }
    public GQAP_FY() {

    }

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

    protected override OplModel GetModel(OplFactory factory, OplSettings settings, Cplex cplex) {
      using (var modelSource = factory.CreateOplModelSourceFromString(model, "gqap_fy"))
      using (var def = factory.CreateOplModelDefinition(modelSource, settings))
        return factory.CreateOplModel(def, cplex);
    }

    private const string model = @"/*********************************************
 * OPL 12.7.0.0 Model
 * Author: Andreas Beham
 * Creation Date: 31.10.2017 at 14:30:01
 *********************************************/

int EQUIPMENTS = ...;
int LOCATIONS = ...;
float TC = ...;

range N = 1..EQUIPMENTS;
range M = 1..LOCATIONS;

float weights[N][N] = ...;
float distances[M][M] = ...;
float install[N][M] = ...;
float demands[N] = ...;
float capacities[M] = ...;

dvar int+ x[N][M] in 0..1;
dvar float+ z[N][M][N][M] in 0..1;

dexpr float installCosts = sum(i in N, k in M) x[i][k] * install[i][k];
dexpr float flowCosts = TC * sum(i in 1..EQUIPMENTS-1, k in M, j in N, h in M: j > i)
  (weights[i][j] * distances[k][h] + weights[j][i] * distances[h][k]) * z[i][k][j][h];

minimize installCosts + flowCosts;
  
subject to {

forall (i in N)
  AllAssigned:
  sum(k in M) x[i][k] == 1;

forall (k in M)
  Capacity:
  sum(i in N) x[i][k] * demands[i] <= capacities[k];

forall (i in 1..EQUIPMENTS-1, k in M, j in N: j > i)
  sum(h in M) z[i][k][j][h] == x[i][k];

forall (i in 1..EQUIPMENTS-1, j in N, h in M: j > i)
  sum(k in M) z[i][k][j][h] == x[j][h];
 
}

";
  }
}