Influence of gene-linkage and recombination of evolutionary algorithms on the rate of evolution, genetic diversity and the response of evolving populations to disturbance

This source preferred by Rick Stafford

Authors: Stafford, R.

Journal: Ecological Informatics

Volume: 1

Pages: 349-354

ISSN: 1574-9541

DOI: 10.1016/j.ecoinf.2006.07.001

This data was imported from Scopus:

Authors: Stafford, R.

Journal: Ecological Informatics

Volume: 1

Issue: 4

Pages: 349-354

ISSN: 1574-9541

DOI: 10.1016/j.ecoinf.2006.07.001

Both biological populations and fault tolerant evolvable hardware systems need to respond rapidly to changes in their dynamic environmental niche. Such changes can be caused by a disturbance event or fault occurring. Here I examine evolutionary algorithms, based on eukaryote sexual selection, which allow different levels of recombination of 'genes'. The differences in recombination are based on 'genes' related to the optimisation process being either linked on a single 'chromosome' or being present on separate 'chromosomes'. When genes are present on separate chromosomes the initial rate of evolution of a randomly generated population is faster than if the genes are linked on the same chromosome. However, when the optimisation problem is changed during the optimisation period, indicating a disturbance or fault occurring, the initial fitness of the linked population is higher and the rate of optimisation immediately after the disturbance is more rapid than for the non-linked populations. The genotypic and phenotypic diversity of the linked populations are also significantly higher immediately prior to the disturbance event. I propose this diversity provides the necessary variation to allow more rapid evolution following a disturbance. The results demonstrate the importance of population diversity in response to change, supporting theory from conservation biology. © 2006 Elsevier B.V. All rights reserved.

This data was imported from Web of Science (Lite):

Authors: Stafford, R.

Journal: ECOLOGICAL INFORMATICS

Volume: 1

Issue: 4

Pages: 349-354

eISSN: 1878-0512

ISSN: 1574-9541

DOI: 10.1016/j.ecoinf.2006.07.001

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