Genetic Programming and Evolvable Machines

, Volume 4, Issue 1, pp 21–51

An Empirical Study of Multipopulation Genetic Programming

  • Francisco Fernández
  • Marco Tomassini
  • Leonardo Vanneschi
Article

DOI: 10.1023/A:1021873026259

Cite this article as:
Fernández, F., Tomassini, M. & Vanneschi, L. Genetic Programming and Evolvable Machines (2003) 4: 21. doi:10.1023/A:1021873026259

Abstract

This paper presents an experimental study of distributed multipopulation genetic programming. Using three well-known benchmark problems and one real-life problem, we discuss the role of the parameters that characterize the evolutionary process of standard panmictic and parallel genetic programming. We find that distributing individuals between subpopulations offers in all cases studied here an advantage both in terms of the quality of solutions and of the computational effort spent, when compared to single populations. We also study the influence of communication patterns such as the communication topology, the number of individuals exchanged and the frequency of exchange on the evolutionary process. We empirically show that the topology does not have a marked influence on the results for the test cases studied here, while the frequency and number of individuals exchanged are related and there exists a suitable range for those parameters which is consistently similar for all the problems studied.

genetic programming distributed evolutionary algorithms parallel algorithms structured populations 

Copyright information

© Kluwer Academic Publishers 2003

Authors and Affiliations

  • Francisco Fernández
    • 1
  • Marco Tomassini
    • 2
  • Leonardo Vanneschi
    • 2
  1. 1.Centro Universitario de MéridaUniversity of ExtremaduraSpain
  2. 2.Computer Science InstituteUniversity of LausanneSwitzerland

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