The performance of polyploid evolutionary algorithms is improved both by having many chromosomes and by having many copies of each chromosome on symbolic regression problems

R Cavill, S Smith, A Tyrrell

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents important new findings for a new method for evolving individual programs with multiple chromosomes. Previous results have shown that evolving individuals with multiple chromosomes produced improved results over evolving individuals with a single chromosome. The multiple chromosomes are organised along two axes; there are a number of different chromosomes and a number of copies of each chromosome. This paper investigates the effects which these two axes have on the performance of the algorithm; whether the improvement in performance comes from just one of these features or whether it is a combination of them both.

Original languageEnglish
Title of host publication2005 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-3, PROCEEDINGS
Place of PublicationNEW YORK
PublisherIEEE
Pages935-941
Number of pages7
ISBN (Print)0-7803-9363-5
Publication statusPublished - 2005
EventIEEE Congress on Evolutionary Computation - Edinburgh
Duration: 2 Sep 20055 Sep 2005

Conference

ConferenceIEEE Congress on Evolutionary Computation
CityEdinburgh
Period2/09/055/09/05

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