Linear bilevel programming technology : models and algorithms

Shi, C

Linear bilevel programming technology : models and algorithms

Shi, C

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Publication Type:: Thesis
Issue Date:: 2005

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Field	Value	Language
dc.contributor.author	Shi, C
dc.date.accessioned	2015-10-26T03:00:38Z
dc.date.available	2015-10-26T03:00:38Z
dc.date.issued	2005
dc.identifier.uri	http://hdl.handle.net/10453/37580
dc.description	University of Technology, Sydney. Faculty of Information Technology.	en_US
dc.description	NO FULL TEXT AVAILABLE. Access is restricted indefinitely. The hardcopy may be available for consultation at the UTS Library.
dc.description.abstract	NO FULL TEXT AVAILABLE. Access is restricted indefinitely. ----- Bilevel programming technology has mainly been developed for solving decision problems with decision makers in a hierarchical organization. This dissertation addresses both theory and technology of linear bilevel programming. It first proposes a new definition of solution and related theorems for linear bilevel programming problems to overcome a fundamental deficiency of existing linear bilevel programming theory. It then presents a comprehensive framework for linear bilevel multifollower programming (BLMFP) problems including ten linear BLMFP models. These models are classified into four types, namely linear BLP, linear BLMFP without shared variables among followers, linear BLMFP with shared variables among followers, and linear BLMFP with partial shared variables among followers. Further, this dissertation proposes related theory and a set of approaches including the Kuhn-Tucker approach, Kth-best approach and branch and bound algorithm for solving each type of the models. Finally, this research develops a prototype of web-based linear bilevel decision support systems by integrating the web, databases and decision support system technologies with the proposed solution approaches of linear BLMFP.	en_US
dc.format	Thesis (PhD)	en_US
dc.language.iso	en	en_US
dc.rights	The author owns the copyright in this thesis including all reproduction and reuse rights for the work. The work may not be altered without the permission of the copyright owner. Attribution is essential when quoting or paraphrasing from this thesis.
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Linear bilevel programming technology : models and algorithms	en_US
dc.type	Thesis
utslib.copyright.status	closed_access

Abstract:

NO FULL TEXT AVAILABLE. Access is restricted indefinitely. ----- Bilevel programming technology has mainly been developed for solving decision problems with decision makers in a hierarchical organization. This dissertation addresses both theory and technology of linear bilevel programming. It first proposes a new definition of solution and related theorems for linear bilevel programming problems to overcome a fundamental deficiency of existing linear bilevel programming theory. It then presents a comprehensive framework for linear bilevel multifollower programming (BLMFP) problems including ten linear BLMFP models. These models are classified into four types, namely linear BLP, linear BLMFP without shared variables among followers, linear BLMFP with shared variables among followers, and linear BLMFP with partial shared variables among followers. Further, this dissertation proposes related theory and a set of approaches including the Kuhn-Tucker approach, Kth-best approach and branch and bound algorithm for solving each type of the models. Finally, this research develops a prototype of web-based linear bilevel decision support systems by integrating the web, databases and decision support system technologies with the proposed solution approaches of linear BLMFP.

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http://hdl.handle.net/10453/37580