source: branches/1614_GeneralizedQAP/HeuristicLab.Problems.GeneralizedQuadraticAssignment.Algorithms/3.3/CPLEX/GQAP-KB.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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#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("KB-Linearization CPLEX (GQAP)", "")]
  [StorableClass]
  [Creatable(CreatableAttribute.Categories.Algorithms)]
  public sealed class GQAP_KB : CplexSolver {
    
    [StorableConstructor]
    private GQAP_KB(bool deserializing) : base(deserializing) { }
    private GQAP_KB(GQAP_KB original, Cloner cloner)
    : base(original, cloner) {
    }
    public GQAP_KB() {

    }

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

    protected override OplModel GetModel(OplFactory factory, OplSettings settings, Cplex cplex) {
      using (var modelSource = factory.CreateOplModelSourceFromString(model, "gqap_kb"))
      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] = ...;

float v[i in N][k in M] = sum(j in N, h in M) (weights[i][j] * distances[k][h]);

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

dexpr float installCosts = sum(i in N, k in M) x[i][k] * install[i][k];
dexpr float flowCosts = TC * sum(i in N, k in M) y[i][k];

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 N, k in M)
  v[i][k] * ( x[i][k] - 1 ) + sum(j in N, h in M) (x[j][h] * weights[i][j] * distances[k][h]) <= y[i][k];

}

";
  }
}