'On the Application of Hierarchical Coevolutionary Genetic Algorithms: Recombination and Evaluation Partners'
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 poten...
| Main Authors: | , |
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| Format: | Article |
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2003
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| Online Access: | https://eprints.nottingham.ac.uk/286/ |
| _version_ | 1848790386920652800 |
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| author | Aickelin, Uwe Bull, Larry |
| author_facet | Aickelin, Uwe Bull, Larry |
| author_sort | Aickelin, Uwe |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-14T18:11:48Z |
| format | Article |
| id | nottingham-286 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T18:11:48Z |
| publishDate | 2003 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-2862020-05-04T20:31:55Z https://eprints.nottingham.ac.uk/286/ 'On the Application of Hierarchical Coevolutionary Genetic Algorithms: Recombination and Evaluation Partners' Aickelin, Uwe Bull, Larry 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. 2003 Article PeerReviewed 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. Genetic Algorithms Coevolution Scheduling |
| spellingShingle | Genetic Algorithms Coevolution Scheduling Aickelin, Uwe Bull, Larry 'On the Application of Hierarchical Coevolutionary Genetic Algorithms: Recombination and Evaluation Partners' |
| title | 'On the Application of Hierarchical Coevolutionary Genetic Algorithms: Recombination and Evaluation Partners' |
| title_full | 'On the Application of Hierarchical Coevolutionary Genetic Algorithms: Recombination and Evaluation Partners' |
| title_fullStr | 'On the Application of Hierarchical Coevolutionary Genetic Algorithms: Recombination and Evaluation Partners' |
| title_full_unstemmed | 'On the Application of Hierarchical Coevolutionary Genetic Algorithms: Recombination and Evaluation Partners' |
| title_short | 'On the Application of Hierarchical Coevolutionary Genetic Algorithms: Recombination and Evaluation Partners' |
| title_sort | 'on the application of hierarchical coevolutionary genetic algorithms: recombination and evaluation partners' |
| topic | Genetic Algorithms Coevolution Scheduling |
| url | https://eprints.nottingham.ac.uk/286/ |