Please use this identifier to cite or link to this item: http://buratest.brunel.ac.uk/handle/2438/5846
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dc.contributor.authorYang, S-
dc.date.accessioned2011-09-23T11:13:11Z-
dc.date.available2011-09-23T11:13:11Z-
dc.date.issued2006-
dc.identifier.citationIEEE Congress on Evolutionary Computation (CEC 2006), Vancouver, BC: 1362 - 1369, Sep 2006en_US
dc.identifier.isbn0-7803-9487-9-
dc.identifier.urihttp://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1688467en
dc.identifier.urihttp://bura.brunel.ac.uk/handle/2438/5846-
dc.descriptionTihis article is posted here with permission from the IEEE - Copyright @ 2006 IEEEen_US
dc.description.abstractUsing diploidy and dominance is one method to enhance the performance of genetic algorithms in dynamic environments. For diploidy genetic algorithms, there are two key design factors: the cardinality of genotypic alleles and the uncertainty in the dominance scheme. This paper investigates the effect of these two factors on the performance of diploidy genetic algorithms in dynamic environments. A generalized diploidy and dominance scheme is proposed for diploidy genetic algorithms, where the cardinality of genotypic alleles and/or the uncertainty in the dominance scheme can be easily tuned and studied. The experimental results show the efficiency of increasing genotypic cardinality rather than introducing uncertainty in the dominance scheme.en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectGenetic algorithmsen_US
dc.titleOn the design of diploid genetic algorithms for problem optimization in dynamic environmentsen_US
dc.typeResearch Paperen_US
dc.identifier.doihttp://dx.doi.org/10.1109/CEC.2006.1688467-
pubs.organisational-data/Brunel-
pubs.organisational-data/Brunel/Brunel (Active)-
pubs.organisational-data/Brunel/Brunel (Active)/School of Info. Systems, Comp & Maths-
pubs.organisational-data/Brunel/Research Centres (RG)-
pubs.organisational-data/Brunel/Research Centres (RG)/CIKM-
pubs.organisational-data/Brunel/School of Information Systems, Computing and Mathematics (RG)-
pubs.organisational-data/Brunel/School of Information Systems, Computing and Mathematics (RG)/CIKM-
Appears in Collections:Publications
Computer Science
Dept of Computer Science Research Papers

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