Skip to main content
SpringerLink
Log in

Selection schemes with spatial isolation for genetic optimization

  • Modification and Extensions to Evolutionary Algorithms
  • Conference paper
  • First Online:
Book cover Parallel Problem Solving from Nature — PPSN III (PPSN 1994)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 866))

Included in the following conference series:

Abstract

We tested genetic algorithms with several selection schemes on a massively multimodal spin-lattice problem. New schemes that introduce a spatial separation between the members of the population gave significantly better results than any other scheme considered. These schemes slow down considerably the flow of genetic information between different regions of the population, which makes possible for distant regions to evolve more or less independently. This way many distinct possibilities can be explored simultaneously and a high degree of diversity can be maintained, which is very important for most multimodal problems.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. K. F. Pál: Genetic algorithms with local optimization. Submitted to Biol. Cybern.

    Google Scholar 

  2. F. Montoya, J.-M. Dubois: Darwinian adaptive simulated annealing. Europhys. Lett. 22 (1993) 79–84.

    Google Scholar 

  3. J. H. Holland: Adaptation in natural and artificial systems. The University of Michigan Press, Ann Arbor, 1975.

    Google Scholar 

  4. D. E. Goldberg: Genetic algorithms in search, optimization and machine learning. Addison-Wesley, Reading, 1989.

    Google Scholar 

  5. D. E. Goldberg: Genetic algorithms and Walsh functions: part II, deception and its analysis. Complex Systems 3 (1989) 153–171.

    MathSciNet  Google Scholar 

  6. A. Brindle: Genetic algorithms for function optimization. Unpublished doctoral dissertation, University of Alberta, Edmonton, 1981.

    Google Scholar 

  7. K. F. Pál: Genetic algorithms for the traveling salesman problem based on a heuristic crossover operation. Biol Cybern 69 (1993) 539–546.

    Article  Google Scholar 

  8. D. Whitley: The Genitor algorithm and selection pressure: Why rank-based allocation of reproductive trials is best. In: J. D. Schaffer (ed.): Proceedings of the third international conference on genetic algorithms. George Mason University 1989, pp. 116–121.

    Google Scholar 

  9. S. W. Mahfoud: Crowding and preselection revisited. Parallel Problem Solving from Nature 2 (1992) 27–36.

    Google Scholar 

  10. D.E. Goldberg, K. Deb: A comparative analysis of selection schemes used in genetic algorithms. In: G. J. E. Rawlins (ed.): Foundations of genetic algorithms. San Mateo, California: Morgan Kaufmann Publishers 1991, pp. 69–93.

    Google Scholar 

  11. G. Syswerda: Uniform crossover in genetic algorithms. In: J. D. Schaffer (ed.): Proceedings of the third international conference on genetic algorithms. George Mason University 1989, pp. 2–9.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institute of Nuclear Research of the Hungarian Academy of Sciences, PO Box 51, H-4001, Debrecen, Hungary

    Károly F. Pál

Authors
  1. Károly F. Pál
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Yuval Davidor Hans-Paul Schwefel Reinhard Männer

Rights and permissions

Reprints and permissions

Copyright information

© 1994 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Pál, K.F. (1994). Selection schemes with spatial isolation for genetic optimization. In: Davidor, Y., Schwefel, HP., Männer, R. (eds) Parallel Problem Solving from Nature — PPSN III. PPSN 1994. Lecture Notes in Computer Science, vol 866. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-58484-6_261

Download citation

  • DOI: https://doi.org/10.1007/3-540-58484-6_261

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-58484-1

  • Online ISBN: 978-3-540-49001-2

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation