Simplified swarm optimization with differential evolution mutation strategy for parameter search

Chang, P; Yeh, W

Simplified swarm optimization with differential evolution mutation strategy for parameter search

Chang, P Yeh, W

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Publisher:: AMC
Publication Type:: Conference Proceeding
Citation:: Proceedings of the 7th International Conference on Ubiquitous Information Management and Communication, 2013, pp. 1 - 5
Issue Date:: 2013-01

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Field	Value	Language
dc.contributor.author	Chang, P	en_US
dc.contributor.author	Yeh, W	en_US
dc.contributor.editor	Ismail, SHLLHR	en_US
dc.date	2013-01-17	en_US
dc.date.issued	2013-01	en_US
dc.identifier.citation	Proceedings of the 7th International Conference on Ubiquitous Information Management and Communication, 2013, pp. 1 - 5	en_US
dc.identifier.isbn	978-1-4503-1958-4	en_US
dc.identifier.uri	http://hdl.handle.net/10453/28357
dc.description.abstract	In practical applications, solving dynamic optimization problem is a challenging field. In recent decades, the optimization approach is not merely dealing with unimodal functions, but also multimodal functions. Even more, the performance of optimization	en_US
dc.publisher	AMC	en_US
dc.relation.ispartof	Proceedings of the 7th International Conference on Ubiquitous Information Management and Communication	en_US
dc.relation.ispartof	International Conference on Ubiquitous Information Management and Communication	en_US
dc.relation.isbasedon	10.1145/2448556.2448581	en_US
dc.title	Simplified swarm optimization with differential evolution mutation strategy for parameter search	en_US
dc.type	Conference Proceeding
utslib.location	USA	en_US
utslib.location.activity	Kota Kinabalu, Malaysia	en_US
utslib.for	0805 Distributed Computing	en_US
dc.location.activity	Kota Kinabalu, Malaysia	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Software
pubs.organisational-group	/University of Technology Sydney/Strength - AAI - Advanced Analytics Institute Research Centre
utslib.copyright.status	closed_access
pubs.consider-herdc	true	en_US
pubs.place-of-publication	USA	en_US
pubs.start-date	2013-01-17	en_US

Abstract:

In practical applications, solving dynamic optimization problem is a challenging field. In recent decades, the optimization approach is not merely dealing with unimodal functions, but also multimodal functions. Even more, the performance of optimization

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http://hdl.handle.net/10453/28357