A hierarchical evolutionary approach to multi-objective optimization

Mumford, Christine Lesley ORCID: https://orcid.org/0000-0002-4514-0272 2004. A hierarchical evolutionary approach to multi-objective optimization. Presented at: CEC2004: Congress on Evolutionary Computation 2004, Portland, OR, USA, 19-23 June 2004. CEC2004: Proceedings of the 2004 Congress on Evolutionary Computation. CEC2004: Proceedings of the 2004 congress on evolutionary computation: Vols 1 and 2. , vol.2 Piscataway, NJ: IEEE, pp. 1944-1951. 10.1109/CEC.2004.1331134

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Abstract

This paper describes a hierarchical evolutionary approach to Pareto-based multi-objective optimization. Using the SEAMO algorithm (a simple evolutionary algorithm for multiobjective optimization) as a basis, it demonstrates how it is possible to obtain a better spread of results if subpopulations of various sizes are used in a simple hierarchical framework. Three alternative hierarchical models are tried and the results compared.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Publication
Status:	Published
Schools:	Computer Science & Informatics
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software
Uncontrolled Keywords:	Pareto-based multiobjective optimization, SEAMO algorithm, hierarchical evolutionary computing
Publisher:	IEEE
ISBN:	0780385152
Last Modified:	20 Oct 2022 09:23
URI:	https://orca.cardiff.ac.uk/id/eprint/31785

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