A λ-cut approximate algorithm for goal-based bilevel risk management systems

Gao, Y; Zhang, G; Lu, J; Dillon, T; Zeng, X

A λ-cut approximate algorithm for goal-based bilevel risk management systems

Gao, Y Zhang, G

Lu, J

Dillon, T Zeng, X

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Publication Type:: Journal Article
Citation:: International Journal of Information Technology and Decision Making, 2008, 7 (4), pp. 589 - 610
Issue Date:: 2008-12-01

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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.contributor.author	Dillon, T	en_US
dc.contributor.author	Zeng, X	en_US
dc.date.issued	2008-12-01	en_US
dc.identifier.citation	International Journal of Information Technology and Decision Making, 2008, 7 (4), pp. 589 - 610	en_US
dc.identifier.issn	0219-6220	en_US
dc.identifier.uri	http://hdl.handle.net/10453/9086
dc.description.abstract	Bilevel programming techniques are developed for decentralized decision problems with decision makers located in two levels. Both upper and lower decision makers, termed as leader and follower, try to optimize their own objectives in solution procedure but are affected by those of the other levels. When a bilevel decision model is built with fuzzy coefficients and the leader and/or follower have goals for their objectives, we call it fuzzy goal bilevel (FGBL) decision problem. This paper first proposes a λ-cut set based FGBL model. A programmable λ-cut approximate algorithm is then presented in detail. Based on this algorithm, a FGBL software system is developed to reach solutions for FGBL decision problems. Finally, two examples are given to illustrate the application of the proposed algorithm. © 2008 World Scientific Publishing Company.	en_US
dc.relation	http://purl.org/au-research/grants/arc/DP0557154
dc.relation.ispartof	International Journal of Information Technology and Decision Making	en_US
dc.relation.isbasedon	10.1142/S0219622008003113	en_US
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.title	A λ-cut approximate algorithm for goal-based bilevel risk management systems	en_US
dc.type	Journal Article
utslib.citation.volume	4	en_US
utslib.citation.volume	7	en_US
utslib.for	080108 Neural, Evolutionary and Fuzzy Computation	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
utslib.for	1503 Business and Management	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/Faculty of Engineering and Information Technology/School of Software
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
utslib.copyright.status	closed_access
pubs.issue	4	en_US
pubs.publication-status	Published	en_US
pubs.volume	7	en_US

Abstract:

Bilevel programming techniques are developed for decentralized decision problems with decision makers located in two levels. Both upper and lower decision makers, termed as leader and follower, try to optimize their own objectives in solution procedure but are affected by those of the other levels. When a bilevel decision model is built with fuzzy coefficients and the leader and/or follower have goals for their objectives, we call it fuzzy goal bilevel (FGBL) decision problem. This paper first proposes a λ-cut set based FGBL model. A programmable λ-cut approximate algorithm is then presented in detail. Based on this algorithm, a FGBL software system is developed to reach solutions for FGBL decision problems. Finally, two examples are given to illustrate the application of the proposed algorithm. © 2008 World Scientific Publishing Company.

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http://hdl.handle.net/10453/9086