Skip to main content

A Schema Theorem-Type Result for Multidimensional Crossover

  • Conference paper
  • 466 Accesses

Abstract

Most of the genetic algorithms (GAs) used in practice work on linear chromosomes (e.g. binary strings or sequences of some other types of symbols). However some results have been published revealing that for certain problems multidimensional encoding and crossover may give better results than the one dimensional (linear) ones [1, 2, 3]. While some theoretical results have been obtained, no clear criteria are known for deciding the suitable dimensionality of the encoding to be used for a given problem.

In this paper we consider a class of problems for which we define a multidimensional encoding and a corresponding genetic operator. We show that for a genetic algorithm (GA) using this encoding and operator we can obtain theoretical results similar to (under certain conditions even better than) those known for linear encoding. We demonstrate these theoretical results using a set of test examples.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. C.A. Anderson, K.F. Jones, and J. Ryan. A two-dimensional genetic algorithm for the ising problem. Complex Systems, 1991.

    Google Scholar 

  2. M. E. Balázs. Genetic Algorithms Theory and Applications. PhD thesis, Babeş-Bolyai University, Romania, 1994.

    Google Scholar 

  3. T.N. Bui and B.R. Moon. On multi-dimensional encoding/crossover. In Proceedings of the Sixth International Conference on Genetic Algorithms, 1995.

    Google Scholar 

  4. L. Davis, editor. Handbook of Genetic Algorithms. Van Nostrand Reinhold, 1991.

    Google Scholar 

  5. K.A. De Jong and W.M. Spears. A formal analysis of the role of multi-point crossover in genetic algorithms. Annals of Mathematics and Artificial Intelligence, 5(1):1–26, 1992.

    Article  MATH  Google Scholar 

  6. D.A. Goldberg. Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley, 1989.

    Google Scholar 

  7. J.H. Holland. Adaptation in the Natural and Artificial Systems. Ann Arbor: University of Michigan Press, 1975.

    Google Scholar 

  8. A.B. Khang and B.R. Moon. Toward more powerful recombinations. In Proceedings of the Sixth International Conference on Genetic Algorithms, 1995.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

Copyright information

© 1998 Springer-Verlag Wien

About this paper

Cite this paper

Balázs, ME. (1998). A Schema Theorem-Type Result for Multidimensional Crossover. In: Artificial Neural Nets and Genetic Algorithms. Springer, Vienna. https://doi.org/10.1007/978-3-7091-6492-1_35

Download citation

  • DOI: https://doi.org/10.1007/978-3-7091-6492-1_35

  • Publisher Name: Springer, Vienna

  • Print ISBN: 978-3-211-83087-1

  • Online ISBN: 978-3-7091-6492-1

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics