Full Elite Sets for Multi-Objective Optimisation

dc.contributor.author	Everson, Richard M.
dc.contributor.author	Fieldsend, Jonathan E.
dc.contributor.author	Singh, Sameer
dc.date.accessioned	2013-07-09T14:53:49Z
dc.date.issued	2002-04-18
dc.description.abstract	Multi-objective evolutionary algorithms frequently use an archive of non-dominated solutions to approximate the Pareto front. We show that the truncation of this archive to a limited number of solutions can lead to oscillating and shrinking estimates of the Pareto front. New data structures to permit efficient query and update of the full archive are proposed, and the superior quality of frontal estimates found using the full archive is illustrated on test problems.	en_GB
dc.identifier.citation	Adaptive Computing in Design and Manufacture V, pp. 343–354	en_GB
dc.identifier.doi	10.1007/978-0-85729-345-9_29
dc.identifier.uri	http://hdl.handle.net/10871/11641
dc.language.iso	en	en_GB
dc.publisher	Springer	en_GB
dc.title	Full Elite Sets for Multi-Objective Optimisation	en_GB
dc.type	Conference paper	en_GB
dc.date.available	2013-07-09T14:53:49Z
dc.identifier.isbn	9781852336059
dc.identifier.isbn	9780857293459
dc.description	Copyright © 2002 Springer. The final publication is available at link.springer.com	en_GB