Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/14478

TitleNovel fish swarm heuristics for bound constrained global optimization problems
Author(s)Rocha, Ana Maria A. C.
Fernandes, Edite Manuela da G. P.
Martins, Tiago F. M. C.
KeywordsGlobal optimization
Derivative-free method
Swarm intelligence
Heuristics
Issue date18-Nov-2011
PublisherSpringer
JournalLecture Notes in Computer Science
Abstract(s)The heuristics herein presented are modified versions of the artificial fish swarm algorithm for global optimization. The new ideas aim to improve solution accuracy and reduce computational costs, in particular the number of function evaluations. The modifications also focus on special point movements, such as the random, search and the leap movements. A local search is applied to refine promising regions. An extension to bound constrained problems is also presented. To assess the performance of the two proposed heuristics, we use the performance profiles as proposed by Dolan and More in 2002. A comparison with three stochastic methods from the literature is included.
TypeConference paper
URIhttp://hdl.handle.net/1822/14478
ISBN9783642219306
DOI10.1007/978-3-642-21931-3_16
ISSN0302-9743
Publisher versionwww.springerlink.com
Peer-Reviewedyes
AccessOpen access
Appears in Collections:LES/ALG - Artigos em revistas científicas internacionais com arbitragem

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