Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/14874

TitleMutation-based artificial fish swarm algorithm for bound constrained global optimization
Author(s)Rocha, Ana Maria A. C.
Fernandes, Edite Manuela da G. P.
KeywordsGlobal optimization
Artificial fish swarm
Mutation
Issue dateSep-2011
PublisherAIP Publishing
JournalAIP Conference Proceedings
Abstract(s)The herein presented mutation-based artificial fish swarm (AFS) algorithm includes mutation operators to prevent the algorithm to falling into local solutions, diversifying the search, and to accelerate convergence to the global optima. Three mutation strategies are introduced into the AFS algorithm to define the trial points that emerge from random, leaping and searching behaviors. Computational results show that the new algorithm outperforms other well-known global stochastic solution methods.
TypeConference paper
URIhttp://hdl.handle.net/1822/14874
ISBN978-0-7354-0956-9
DOI10.1063/1.3636841
ISSN0094-243X
Publisher versionhttp://proceedings.aip.org/
Peer-Reviewedyes
AccessOpen access
Appears in Collections:LES/ALG - Capítulos de livros

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