Automatic Configuration of Multi-Objective ACO Algorithms

  • Manuel López-Ibáñez
  • Thomas Stützle
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6234)

Abstract

In the last few years a significant number of ant colony optimization (ACO) algorithms have been proposed for tackling multi-objective optimization problems. In this paper, we propose a software framework that allows to instantiate the most prominent multi-objective ACO (MOACO) algorithms. More importantly, the flexibility of this MOACO framework allows the application of automatic algorithm configuration techniques. The experimental results presented in this paper show that such an automatic configuration of MOACO algorithms is highly desirable, given that our automatically configured algorithms clearly outperform the best performing MOACO algorithms that have been proposed in the literature. As far as we are aware, this paper is also the first to apply automatic algorithm configuration techniques to multi-objective stochastic local search algorithms.

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References

  1. 1.
    Alaya, I., Solnon, C., Ghédira, K.: Ant colony optimization for multi-objective optimization problems. In: 19th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2007), vol. 1, pp. 450–457. IEEE Computer Society Press, Los Alamitos (2007)CrossRefGoogle Scholar
  2. 2.
    Barán, B., Schaerer, M.: A multiobjective ant colony system for vehicle routing problem with time windows. In: Proceedings of the Twenty first IASTED International Conference on Applied Informatics, Insbruck, Austria, pp. 97–102 (2003)Google Scholar
  3. 3.
    Bartz-Beielstein, T., Chiarandini, M., Paquete, L., Preuß, M. (eds.): Experimental Methods for the Analysis of Optimization Algorithms. Springer, Heidelberg (2010)Google Scholar
  4. 4.
    Birattari, M., Yuan, Z., Balaprakash, P., Stützle, T.: F-race and iterated F-race: An overview. In: Bartz-Beielstein, et al [3] (to appear)Google Scholar
  5. 5.
    Doerner, K.F., Gutjahr, W.J., Hartl, R.F., Strauss, C., Stummer, C.: Pareto ant colony optimization: A metaheuristic approach to multiobjective portfolio selection. Annals of Operations Research 131, 79–99 (2004)MATHCrossRefMathSciNetGoogle Scholar
  6. 6.
    Doerner, K.F., Hartl, R.F., Reimann, M.: Are CompetAnts more competent for problem solving? The case of a multiple objective transportation problem. Central European Journal for Operations Research and Economics 11(2), 115–141 (2003)MATHMathSciNetGoogle Scholar
  7. 7.
    Dorigo, M., Stützle, T.: Ant Colony Optimization. MIT Press, Cambridge (2004)MATHGoogle Scholar
  8. 8.
    García-Martínez, C., Cordón, O., Herrera, F.: A taxonomy and an empirical analysis of multiple objective ant colony optimization algorithms for the bi-criteria TSP. European Journal of Operational Research 180(1), 116–148 (2007)MATHCrossRefGoogle Scholar
  9. 9.
    Grunert da Fonseca, V., Fonseca, C.M., Hall, A.O.: Inferential performance assessment of stochastic optimisers and the attainment function. In: Zitzler, et al [19], pp. 213–225Google Scholar
  10. 10.
    Iredi, S., Merkle, D., Middendorf, M.: Bi-criterion optimization with multi colony ant algorithms. In: Zitzler, et al [19], pp. 359–372Google Scholar
  11. 11.
    KhudaBukhsh, A.R., Xu, L., Hoos, H.H., Leyton-Brown, K.: SATenstein: Automatically building local search SAT solvers from components. In: Proc. of the Twenty-First International Joint Conference on Artificial Intelligence (IJCAI 2009), pp. 517–524 (2009)Google Scholar
  12. 12.
    López-Ibáñez, M., Paquete, L., Stützle, T.: On the design of ACO for the biobjective quadratic assignment problem. In: Dorigo, M., Birattari, M., Blum, C., Gambardella, L.M., Mondada, F., Stützle, T. (eds.) ANTS 2004. LNCS, vol. 3172, pp. 214–225. Springer, Heidelberg (2004)Google Scholar
  13. 13.
    López-Ibáñez, M., Paquete, L., Stützle, T.: Hybrid population-based algorithms for the bi-objective quadratic assignment problem. Journal of Mathematical Modelling and Algorithms 5(1), 111–137 (2006)MATHCrossRefMathSciNetGoogle Scholar
  14. 14.
    López-Ibáñez, M., Paquete, L., Stützle, T.: Exploratory analysis of stochastic local search algorithms in biobjective optimization. In: Bartz-Beielstein, et al [3], 209–233Google Scholar
  15. 15.
    López-Ibáñez, M., Stützle, T.: The impact of design choices of multi-objective ant colony optimization algorithms on performance: An experimental study on the biobjective TSP. In: GECCO 2010, pp. 71–78. ACM Press, New York (2010)CrossRefGoogle Scholar
  16. 16.
    López-Ibáñez, M., Stützle, T.: An analysis of algorithmic components for multiobjective ant colony optimization: A case study on the biobjective TSP. In: Collet, P., Legrand, P. (eds.) EA 2009. LNCS, vol. 5975, pp. 134–145. Springer, Heidelberg (2010)Google Scholar
  17. 17.
    Mariano, C.E., Morales, E.: MOAQ: An Ant-Q algorithm for multiple objective optimization problems. In: Banzhaf, W., Daida, J., Eiben, A.E., Garzon, M.H., Honavar, V., Jakiela, M., Smith, R.E. (eds.) Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 1999), vol. 1, pp. 894–901. Morgan Kaufmann Publishers, San Francisco (1999)Google Scholar
  18. 18.
    Stützle, T., Hoos, H.H.: \(\mathcal{MAX -MIN}\). Future Generation Computer Systems 16(8), 889–914 (2000)CrossRefGoogle Scholar
  19. 19.
    Zitzler, E., Deb, K., Thiele, L., Coello, C.A., Corne, D. (eds.): EMO 2001. LNCS, vol. 1993. Springer, Heidelberg (2001)Google Scholar
  20. 20.
    Zitzler, E., Laumanns, M., Thiele, L.: SPEA2: Improving the strength Pareto evolutionary algorithm for multiobjective optimization. In: Giannakoglou, K., et al. (eds.) Proceedings of EUROGEN 2001, International Center for Numerical Methods in Engineering (CIMNE), pp. 95–100 (2002)Google Scholar
  21. 21.
    Zitzler, E., Thiele, L., Laumanns, M., Fonseca, C.M., Grunert da Fonseca, V.: Performance assessment of multiobjective optimizers: an analysis and review. IEEE Transactions on Evolutionary Computation 7(2), 117–132 (2003)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Manuel López-Ibáñez
    • 1
  • Thomas Stützle
    • 1
  1. 1.IRIDIA, CoDEUniversité Libre de BruxellesBrusselsBelgium

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