A λ-CUT APPROXIMATE ALGORITHM FOR GOAL-BASED BILEVEL RISK MANAGEMENT SYSTEMS

Ya Gao (), Guangquan Zhang (), Jie Lu, Tharam Dillon () and Xianyi Zeng ()
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Ya Gao: Faculty of Information Technology, University of Technology, Sydney, PO Box 123, Broadway, NSW 2007, Australia
Guangquan Zhang: Faculty of Information Technology, University of Technology, Sydney, PO Box 123, Broadway, NSW 2007, Australia
Tharam Dillon: Digital Ecosystems and Business Intelligence Institute, Curtin University of Technology, Perth, WA 6845, Australia
Xianyi Zeng: Ecole Nationale Supérieure des Arts et Industries Textiles, 9 rue de l'Ermitage 59100 Roubaix, France

International Journal of Information Technology & Decision Making (IJITDM), 2008, vol. 07, issue 04, 589-610

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.

Keywords: Bilevel decision making; goal programming; fuzzy sets; optimization; risk management (search for similar items in EconPapers)
Date: 2008
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DOI: 10.1142/S0219622008003113

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