The Kth-best approach for linear bilevel multifollower programming with partial shared variables among followers

Shi, Chenggen and Zhou, Hong and Lu, Jie and Zhang, Guangquan and Zhang, Zhongwei (2007) The Kth-best approach for linear bilevel multifollower programming with partial shared variables among followers. Applied Mathematics and Computation, 188 (2). pp. 1686-1698. ISSN 0096-3003

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Abstract

In a real world bilevel decision-making, the lower level of a bilevel decision usually involves multiple decision units. This paper proposes the Kth-best approach for linear bilevel multifollower programming problems with sharing variables among followers. Finally a numeric example is given to show how the Kth-best approach works.

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Item Type:	Article (Commonwealth Reporting Category C)
Refereed:	No
Item Status:	Live Archive
Additional Information:	Author's version deposited in accordance with the copyright policy of the publisher.
Faculty/School / Institute/Centre:	Historic - Faculty of Engineering and Surveying - Department of Electrical, Electronic and Computer Engineering (Up to 30 Jun 2013)
Faculty/School / Institute/Centre:	Historic - Faculty of Engineering and Surveying - Department of Electrical, Electronic and Computer Engineering (Up to 30 Jun 2013)
Date Deposited:	21 Feb 2008 12:29
Last Modified:	02 Aug 2021 05:04
Uncontrolled Keywords:	Linear bilevel programming, mulitfollower, Kth-bestg approach, Von Stackelberg game
Fields of Research (2008):	08 Information and Computing Sciences > 0802 Computation Theory and Mathematics > 080299 Computation Theory and Mathematics not elsewhere classified 01 Mathematical Sciences > 0103 Numerical and Computational Mathematics > 010399 Numerical and Computational Mathematics not elsewhere classified
Fields of Research (2020):	46 INFORMATION AND COMPUTING SCIENCES > 4613 Theory of computation > 461399 Theory of computation not elsewhere classified 49 MATHEMATICAL SCIENCES > 4903 Numerical and computational mathematics > 490399 Numerical and computational mathematics not elsewhere classified
Identification Number or DOI:	https://doi.org/10.1016/j.amc.2006.11.176
URI:	http://eprints.usq.edu.au/id/eprint/1699

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