A particle swarm optimization based algorithm for fuzzy bilevel decision making with constraints-shared followers

Gao, Y; Zhang, G; Lu, J

A particle swarm optimization based algorithm for fuzzy bilevel decision making with constraints-shared followers

Gao, Y Zhang, G

Lu, J

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Publication Type:: Conference Proceeding
Citation:: Proceedings of the ACM Symposium on Applied Computing, 2009, pp. 1075 - 1079
Issue Date:: 2009-12-01

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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	2009-12-01	en_US
dc.identifier.citation	Proceedings of the ACM Symposium on Applied Computing, 2009, pp. 1075 - 1079	en_US
dc.identifier.isbn	9781605581668	en_US
dc.identifier.uri	http://hdl.handle.net/10453/10868
dc.description.abstract	In a bilevel decision problem, decision making may involve multiple followers and fuzzy demands. This research focuses on the problem of fuzzy linear bilevel decision making with multiple followers who share common constraints (FBCSF). Based on the ranking relationship among fuzzy sets defined by cut set and satisfactory degree α, a FBCSF model is presented and a particle swarm optimization based algorithm is developed. The experiments reveal that solutions obtained by this algorithm are reasonable and stable. Copyright 2009 ACM.	en_US
dc.relation.ispartof	Proceedings of the ACM Symposium on Applied Computing	en_US
dc.relation.isbasedon	10.1145/1529282.1529519	en_US
dc.title	A particle swarm optimization based algorithm for fuzzy bilevel decision making with constraints-shared followers	en_US
dc.type	Conference Proceeding
utslib.for	080108 Neural, Evolutionary and Fuzzy Computation	en_US
utslib.for	080105 Expert Systems	en_US
utslib.for	0804 Data Format	en_US
dc.location.activity	Hawaii, USA	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:

In a bilevel decision problem, decision making may involve multiple followers and fuzzy demands. This research focuses on the problem of fuzzy linear bilevel decision making with multiple followers who share common constraints (FBCSF). Based on the ranking relationship among fuzzy sets defined by cut set and satisfactory degree α, a FBCSF model is presented and a particle swarm optimization based algorithm is developed. The experiments reveal that solutions obtained by this algorithm are reasonable and stable. Copyright 2009 ACM.

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http://hdl.handle.net/10453/10868