Multi-chromosomal genetic programming

Rachel Cavill, Steve Smith, Andy Tyrrell

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


This paper introduces an evolutionary algorithm which uses multiple chromosomes to evolve solutions to a symbolic regression problem. Inspiration for this algorithm is provided by the existence of multiple chromosomes in natural evolution, particularly in plants. A multi-chromosomal system usually requires a dominance system and subsequently dominance in nature and in previous artificial evolutionary systems has also been considered. An implementation of a multi-chromosomal system is presented with initial results which support the use of multi-chromosomal techniques in evolutionary algorithms.

Original languageEnglish
Title of host publicationGECCO 2005: Genetic and Evolutionary Computation Conference, Vols 1 and 2
EditorsHG Beyer
Place of PublicationNEW YORK
Number of pages7
ISBN (Print)1-59593-010-8
Publication statusPublished - 2005
EventGenetic and Evolutionary Computation Conference - Washington
Duration: 25 Jun 200529 Jun 2005


ConferenceGenetic and Evolutionary Computation Conference


  • algorithms performance design
  • genetic programming
  • representations
  • team evolution

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