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'On the Application of Hierarchical Coevolutionary Genetic Algorithms: Recombination and Evaluation Partners'

Aickelin, Uwe; Bull, Larry

Authors

Uwe Aickelin

Larry Bull



Abstract

This paper examines the use of a hierarchical coevolutionary genetic algorithm under different partnering strategies. Cascading clusters of sub-populations are built from the bottom up, with higher-level sub-populations optimising larger parts of the problem. Hence higher-level sub-populations potentially search a larger search space with a lower resolution whilst lower-level sub-populations search a smaller search space with a higher resolution. The effects of different partner selection schemes amongst the sub-populations on solution quality are examined for two constrained optimisation problems. We examine a number of recombination partnering strategies in the construction of higher-level individuals and a number of related schemes for evaluating sub-solutions. It is shown that partnering strategies that exploit problem-specific knowledge are superior and can counter inappropriate (sub-) fitness measurements.

Journal Article Type Article
Publication Date Jan 1, 2003
Journal Journal of Applied System Studies
Peer Reviewed Peer Reviewed
Volume 4
Issue 2
APA6 Citation Aickelin, U., & Bull, L. (2003). 'On the Application of Hierarchical Coevolutionary Genetic Algorithms: Recombination and Evaluation Partners'
Keywords Genetic Algorithms, Coevolution, Scheduling
Copyright Statement Copyright information regarding this work can be found at the following address: http://eprints.nottingh.../end_user_agreement.pdf

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Copyright Statement
Copyright information regarding this work can be found at the following address: http://eprints.nottingham.ac.uk/end_user_agreement.pdf





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