On the Importance of Information Speed in Structured Populations

  • Mike Preuss
  • Christian Lasarczyk
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3242)

Abstract

A radius-based separation of selection and recombination spheres in diffusion model EAs is introduced, enabling a new taxonomy, oriented towards information flow analysis. It also contains parallel hillclimbers, panmictic EA and an unexplored area. Experiments are performed systematically on five complex binary and real coded problems in search of the best performing variants w.r.t. available optimization time. Additionally, information flow through recombination and selection is emulated by means of a simple model, that produces qualitative similar results.

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References

  1. 1.
    Beyer, H.G., Schwefel, H.P.: Evolution strategies: A comprehensive introduction. Journal Natural Computing 1, 3–52 (2002)MATHCrossRefMathSciNetGoogle Scholar
  2. 2.
    Eiben, A.E., Smith, J.E.: Introduction to Evolutionary Computing. Springer, Heidelberg (2003)MATHGoogle Scholar
  3. 3.
    De Jong, K.A.: An analysis of the behavior of a class of genetic adaptive systems. PhD thesis, University of Michigan (1975)Google Scholar
  4. 4.
    Goldberg, D.E., Richardson, J.: Genetic algorithms with sharing for multimodal function optimization. In: Grefenstette, J. (ed.) Genetic Algorithms and their Applications (ICGA 1987), pp. 41–49. Lawrence Erlbaum Associates, Mahwah (1987)Google Scholar
  5. 5.
    Li, J.P., Balazs, M.E., Parks, G.T., Clarkson, P.J.: A species conserving genetic algorithm for multimodal function optimization. Evolutionary Computation 10, 207–234 (2002)CrossRefGoogle Scholar
  6. 6.
    Voudouris, C.: Guided local search – an illustrative example in function optimisation. BT Technology Journal 16, 46–50 (1998)CrossRefGoogle Scholar
  7. 7.
    Lasarczyk, C.W.G., Dittrich, P., Banzhaf, W.: Dynamic subset selection based on a fitness case topology. Evolutionary Computation 12 (2004) (in print)Google Scholar
  8. 8.
    Alba, E., Tomassini, M.: Parallelism and evolutionary algorithms. IEEE Transactions on Evolutionary Computation 6, 443–462 (2002)CrossRefGoogle Scholar
  9. 9.
    Sarma, J., De Jong, K.: An analysis of the effects of neighborhood size and shape on local selection algorithms. In: Ebeling, W., Rechenberg, I., Voigt, H.-M., Schwefel, H.-P. (eds.) PPSN 1996. LNCS, vol. 1141, pp. 236–244. Springer, Heidelberg (1996)CrossRefGoogle Scholar
  10. 10.
    Sprave, J.: Linear neighborhood evolution strategy. In: Sebald, A.V., Fogel, L.J. (eds.) Proc. EP1994, pp. 42–51. World Scientific, Singapore (1994)Google Scholar
  11. 11.
    De Jong, K.A., Potter, M.A., Spears, W.M.: Using problem generators to explore the effects of epistasis. In: Bäck, T. (ed.) ICGA, San Francisco, CA, pp. 338–345. Morgan Kaufmann, San Francisco (1997)Google Scholar
  12. 12.
    De Jong, K.A., Spears, W.M.: An analysis of the interacting roles of population size and crossover in genetic algorithms. In: Schwefel, H.-P., Männer, R. (eds.) PPSN 1990. LNCS, vol. 496, pp. 38–47. Springer, Heidelberg (1991)CrossRefGoogle Scholar
  13. 13.
    Salomon, R.: Re-evaluating genetic algorithm performance under coordinate rotation of benchmark functions: A survey of some theoretical and practical aspects of genetic algorithms. BioSystems 39, 263–278 (1996)CrossRefGoogle Scholar
  14. 14.
    Keane, A.J.: Experiences with optimizers in structural design. In: Parmee, I.C. (ed.) Proc. Adaptive Computing in Engineering Design and Control 1994, Plymouth, UK, pp. 14–27 (1994)Google Scholar
  15. 15.
    Mitchell, D., Selman, B., Levesque, H.: Hard and easy distributions of SAT problems. In: Proceedings of AAAI–1992, San Jose, California, pp. 459–465. AAAI Press, Menlo Park (1992)Google Scholar
  16. 16.
    Watts, D.J., Strogatz, S.H.: Collective dynamics of small–world networks. Nature 393, 440–442 (1998)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Mike Preuss
    • 1
  • Christian Lasarczyk
    • 1
  1. 1.University of DortmundDortmundGermany

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