A particle swarm optimization based algorithm for fuzzy bilevel decision making

Gao, Y; Zhang, G; Lu, J

A particle swarm optimization based algorithm for fuzzy bilevel decision making

Gao, Y Zhang, G

Lu, J

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Publication Type:: Conference Proceeding
Citation:: IEEE International Conference on Fuzzy Systems, 2008, pp. 1452 - 1457
Issue Date:: 2008-11-07

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Field	Value	Language
dc.contributor.author	Gao, Y	en_US
dc.contributor.author	Zhang, G https://orcid.org/0000-0003-3960-0583	en_US
dc.contributor.author	Lu, J https://orcid.org/0000-0003-0690-4732	en_US
dc.date.issued	2008-11-07	en_US
dc.identifier.citation	IEEE International Conference on Fuzzy Systems, 2008, pp. 1452 - 1457	en_US
dc.identifier.isbn	9781424418190	en_US
dc.identifier.issn	1098-7584	en_US
dc.identifier.uri	http://hdl.handle.net/10453/10819
dc.description.abstract	Bilevel decision techniques are developed for decentralized planning problems with decision makers located in a two-level system. This study develops a particle swarm optimization based algorithm to solve fuzzy linear bilevel (FLBL) decision problems. A main advantage of this algorithm is that the optimization technique is adopted directly on FLBL problems by fully considering the original information carried by the fuzzy parameters, thus minimizing information loss. Experiments reveal that this algorithm can effectively solve the fuzzy linear bilevel decision problems. © 2008 IEEE.	en_US
dc.relation.ispartof	IEEE International Conference on Fuzzy Systems	en_US
dc.relation.isbasedon	10.1109/FUZZY.2008.4630563	en_US
dc.title	A particle swarm optimization based algorithm for fuzzy bilevel decision making	en_US
dc.type	Conference Proceeding
utslib.for	080108 Neural, Evolutionary and Fuzzy Computation	en_US
utslib.for	080105 Expert Systems	en_US
dc.location.activity	Kong Kong, China	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 Computer Science
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

Bilevel decision techniques are developed for decentralized planning problems with decision makers located in a two-level system. This study develops a particle swarm optimization based algorithm to solve fuzzy linear bilevel (FLBL) decision problems. A main advantage of this algorithm is that the optimization technique is adopted directly on FLBL problems by fully considering the original information carried by the fuzzy parameters, thus minimizing information loss. Experiments reveal that this algorithm can effectively solve the fuzzy linear bilevel decision problems. © 2008 IEEE.

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http://hdl.handle.net/10453/10819