Parameter Control Methods for Selection Operators in Genetic Algorithms

  • Péter Vajda
  • Agoston E. Eiben
  • Wim Hordijk
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5199)

Abstract

Parameter control is still one of the main challenges in evolutionary computation. This paper is concerned with controlling selection operators on-the-fly. We perform an experimental comparison of such methods on three groups of test functions and conclude that varying selection pressure during a GA run often yields performance benefits, and therefore is a recommended option for designers and users of evolutionary algorithms.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Bäck, T.: Evolutionary algorithms in theory and practice. Oxford University Press, Oxford (1996)MATHGoogle Scholar
  2. 2.
    Bäck, T., Schütz, M.: Intelligent mutation rate control in canonical genetic algorithms. In: Michalewicz, M., Raś, Z.W. (eds.) ISMIS 1996. LNCS, vol. 1079, pp. 158–167. Springer, Heidelberg (1996)CrossRefGoogle Scholar
  3. 3.
    DeJong, K.: Parameter setting in EAs: a 30 year perspective. In: Parameter Setting in Evolutionary Algorithms, pp. 1–18. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  4. 4.
    Eiben, A.E., Hinterding, R., Michalewicz, Z.: Parameter control in evolutionary algorithms. IEEE Transactions on Evolutionary Computation 3(2), 124–141 (1999)CrossRefGoogle Scholar
  5. 5.
    Eiben, A.E., Schut, M.C., de Wilde, A.R.: Boosting genetic algorithms with self-adaptive selection. In: Proceedings of the IEEE Congress on Evolutionary Computation, pp. 1584–1589 (2006)Google Scholar
  6. 6.
    Eiben, A.E., Smith, J.E.: Introduction to Evolutionary Computing, Corrected reprint. Springer, Heidelberg (2007)Google Scholar
  7. 7.
    Yager, R.R., et al.: Fuzzy Sets and Applications: Selected Papers by L.A. Zadeh. John Wiley, New York (1987)Google Scholar
  8. 8.
    Herrera, F., Lozano, M.: Fuzzy genetic algorithms: issues and models. Technical report, No. 18071, Granada, Spain (1999)Google Scholar
  9. 9.
    Hohn, C., Reeves, C.: Are long path problems hard for genetic algorithms? In: Ebeling, W., Rechenberg, I., Voigt, H.-M., Schwefel, H.-P. (eds.) PPSN 1996. LNCS, vol. 1141, pp. 134–143. Springer, Heidelberg (1996)CrossRefGoogle Scholar
  10. 10.
    Holland, J.H.: Adaption in Natural and Artificial Systems. University of Michigan Press (1975)Google Scholar
  11. 11.
    Jansen, T., De Jong, K., Wegener, I.: On the choice of offspring population size in evolutionary algorithms. Evolutionary Computation 13(4), 413–440 (2005)CrossRefGoogle Scholar
  12. 12.
    De Jong, K.A., Spears, W.M.: A formal analysis of the role of multi-point crossover in genetic algorithms. Annals of Mathematics and Artificial Intelligence (5), 1–26 (1992)Google Scholar
  13. 13.
    Lobo, F.G., Lima, C.F., Michalewicz, Z. (eds.): Parameter Setting in Evolutionary Algorithms. Studies in Computational Intelligence, vol. 54. Springer, Heidelberg (2007)MATHGoogle Scholar
  14. 14.
    Mahfoud, S.W., Goldberg, D.E.: Parallel recombinative simulated annealing: a genetic algorithm. Parallel Computing 21(1), 1–28 (1995)CrossRefMATHMathSciNetGoogle Scholar
  15. 15.
    Mitchell, M., Forrest, S., Holland, J.H.: The royal road for genetic algorithms: Fitness landscapes and GA performance. In: Varela, F.J., Bourgine, P. (eds.) Towards a Practice of Autonomous Systems: Proceedings of the First European Conference on Artificial Life, Paris, 11–13, 1992, pp. 245–254. A Bradford book, The MIT Press (1992)Google Scholar
  16. 16.
    Schwefel, H.-P.: Evolution and Optimum Seeking. Wiley, Chichester (1995)Google Scholar
  17. 17.
    Spears, W.: Evolutionary algorithms: the role of mutation and recombination. Springer, Heidelberg (2000)CrossRefGoogle Scholar
  18. 18.
    Whitley, D.: Fundamental principles of deception. In: Morgan Kaufmann (ed.) Foundations of Genetic Algorithms, pp. 221–241. Morgan Kaufmann, San Francisco (1991)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Péter Vajda
    • 1
  • Agoston E. Eiben
    • 1
  • Wim Hordijk
    • 1
  1. 1.Vrije Universiteit AmsterdamNetherlands

Personalised recommendations