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

Aickelin, Uwe and Bull, Larry (2003) 'On the Application of Hierarchical Coevolutionary Genetic Algorithms: Recombination and Evaluation Partners'. Journal of Applied System Studies, 4 (2). pp. 2-17.

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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.

Item Type: Article
Uncontrolled Keywords: Genetic Algorithms, Coevolution, Scheduling
Schools/Departments: University of Nottingham UK Campus > Faculty of Science > School of Computer Science
Depositing User: Aickelin, Professor Uwe
Date Deposited: 07 Nov 2005
Last Modified: 04 Dec 2007 14:28
URI: http://eprints.nottingham.ac.uk/id/eprint/286

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