A λ-cut and goal-programming-based algorithm for fuzzy-linear multiple-objective bilevel optimization

Gao, Y; Zhang, G; Ma, J; Lu, J

A λ-cut and goal-programming-based algorithm for fuzzy-linear multiple-objective bilevel optimization

Gao, Y Zhang, G

Ma, J Lu, J

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Publication Type:: Journal Article
Citation:: IEEE Transactions on Fuzzy Systems, 2010, 18 (1), pp. 1 - 13
Issue Date:: 2010-02-01

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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	Ma, J	en_US
dc.contributor.author	Lu, J https://orcid.org/0000-0003-0690-4732	en_US
dc.date.issued	2010-02-01	en_US
dc.identifier.citation	IEEE Transactions on Fuzzy Systems, 2010, 18 (1), pp. 1 - 13	en_US
dc.identifier.issn	1063-6706	en_US
dc.identifier.uri	http://hdl.handle.net/10453/13466
dc.description.abstract	Bilevel-programming techniques are developed to handle decentralized problems with two-level decision makers, which are leaders and followers, who may have more than one objective to achieve. This paper proposes a λ-cut and goal-programming-based algorithm to solve fuzzy-linear multiple-objective bilevel (FLMOB) decision problems. First, based on the definition of a distance measure between two fuzzy vectors using λ-cut, a fuzzy-linear bilevel goal (FLBG) model is formatted, and related theorems are proved. Then, using a λ-cut for fuzzy coefficients and a goal-programming strategy for multiple objectives, a λ-cut and goal-programming-based algorithm to solve FLMOB decision problems is presented. A case study for a newsboy problem is adopted to illustrate the application and executing procedure of this algorithm. Finally, experiments are carried out to discuss and analyze the performance of this algorithm. © 2006 IEEE.	en_US
dc.relation	http://purl.org/au-research/grants/arc/DP0557154
dc.relation.ispartof	IEEE Transactions on Fuzzy Systems	en_US
dc.relation.isbasedon	10.1109/TFUZZ.2009.2030329	en_US
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.title	A λ-cut and goal-programming-based algorithm for fuzzy-linear multiple-objective bilevel optimization	en_US
dc.type	Journal Article
utslib.citation.volume	1	en_US
utslib.citation.volume	18	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
utslib.for	0102 Applied Mathematics	en_US
utslib.for	0906 Electrical and Electronic Engineering	en_US
dc.location.activity	ISI:000274217500001	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	open_access
pubs.issue	1	en_US
pubs.publication-status	Published	en_US
pubs.volume	18	en_US

Abstract:

Bilevel-programming techniques are developed to handle decentralized problems with two-level decision makers, which are leaders and followers, who may have more than one objective to achieve. This paper proposes a λ-cut and goal-programming-based algorithm to solve fuzzy-linear multiple-objective bilevel (FLMOB) decision problems. First, based on the definition of a distance measure between two fuzzy vectors using λ-cut, a fuzzy-linear bilevel goal (FLBG) model is formatted, and related theorems are proved. Then, using a λ-cut for fuzzy coefficients and a goal-programming strategy for multiple objectives, a λ-cut and goal-programming-based algorithm to solve FLMOB decision problems is presented. A case study for a newsboy problem is adopted to illustrate the application and executing procedure of this algorithm. Finally, experiments are carried out to discuss and analyze the performance of this algorithm. © 2006 IEEE.

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http://hdl.handle.net/10453/13466