The Kth-Best Approach for Linear Bilevel Multi-follower Programming

Authors:
Chenggen Shi;Guangquan Zhang;Jie Lu
Affiliations:
Faculty of Information Technology, University of Technology, Sydney, Australia 2007;Faculty of Information Technology, University of Technology, Sydney, Australia 2007;Faculty of Information Technology, University of Technology, Sydney, Australia 2007
Venue:
Journal of Global Optimization
Year:
2005

Citing 2
Cited 1

New branch-and-bound rules for linear bilevel programming

SIAM Journal on Scientific and Statistical Computing
On bilevel multi-follower decision making: General framework and solutions

Information Sciences: an International Journal

Linear bilevel multi-follower programming with independent followers

Journal of Global Optimization

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Abstract

The majority of research on bilevel programming has centered on the linear version of the problem in which only one leader and one follower are involved. This paper addresses linear bilevel multi-follower programming (BLMFP) problems in which there is no sharing information among followers. It explores the theoretical properties of linear BLMFP, extends the Kth-best approach for solving linear BLMFP problems and gives a computational test for this approach.