Uwe Aickelin
'On the Application of Hierarchical Coevolutionary Genetic Algorithms: Recombination and Evaluation Partners'
Aickelin, Uwe; Bull, Larry
Authors
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.
Citation
Aickelin, U., & Bull, L. (2003). 'On the Application of Hierarchical Coevolutionary Genetic Algorithms: Recombination and Evaluation Partners'
Journal Article Type | Article |
---|---|
Publication Date | Jan 1, 2003 |
Deposit Date | Nov 7, 2005 |
Publicly Available Date | Mar 29, 2024 |
Journal | Journal of Applied System Studies |
Peer Reviewed | Peer Reviewed |
Volume | 4 |
Issue | 2 |
Keywords | Genetic Algorithms, Coevolution, Scheduling |
Public URL | https://nottingham-repository.worktribe.com/output/1022126 |
Files
03jass_partner.pdf
(223 Kb)
PDF
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