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Bilevel transportation modeling and ...

Meng, Qiang.

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Bilevel transportation modeling and optimization.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Bilevel transportation modeling and optimization./
作者:	Meng, Qiang.
面頁冊數:	248 p.
附註:	Adviser: Hai Yang.
Contained By:	Dissertation Abstracts International61-10B.
標題:	Computer Science. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=9991511
ISBN:	0599989270

Bilevel transportation modeling and optimization.
Meng, Qiang.

Bilevel transportation modeling and optimization. - 248 p.

Adviser: Hai Yang.

Thesis (Ph.D.)--Hong Kong University of Science and Technology (People's Republic of China), 2000.

In this dissertation, we focus on the bilevel transportation problem with a network equilibrium constraint that describes the behavior of network users' route choice. From the mathematical viewpoints, the bilevel transportation problem with the network equilibrium constraint can be characterized by the bilevel programming model in which the lower level problem is a nonlinear programming problem that represents the network equilibrium problem. It is well known that the bilevel programming problem is one of the hardest problems to solve in nonlinear programming. Therefore, it is a significant and challenging issue to study the relevant models and algorithms for the bilevel transportation problem by exploring its inherent nature.

ISBN: 0599989270Subjects--Topical Terms:

626642
Computer Science.

Bilevel transportation modeling and optimization.
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245 1 0 $a Bilevel transportation modeling and optimization.
300 $a 248 p.
500 $a Adviser: Hai Yang.
500 $a Source: Dissertation Abstracts International, Volume: 61-10, Section: B, page: 5451.
502 $a Thesis (Ph.D.)--Hong Kong University of Science and Technology (People's Republic of China), 2000.
520 $a In this dissertation, we focus on the bilevel transportation problem with a network equilibrium constraint that describes the behavior of network users' route choice. From the mathematical viewpoints, the bilevel transportation problem with the network equilibrium constraint can be characterized by the bilevel programming model in which the lower level problem is a nonlinear programming problem that represents the network equilibrium problem. It is well known that the bilevel programming problem is one of the hardest problems to solve in nonlinear programming. Therefore, it is a significant and challenging issue to study the relevant models and algorithms for the bilevel transportation problem by exploring its inherent nature.
520 $a First of all, the current state of research is reviewed on models and algorithms in bilevel transportation problem with the network user equilibrium constraint. In general, these existing models and algorithms are classified into seven and four categories, respectively. Secondly, we study the travel demand sensitivity analysis for the deterministic user equilibrium problem that is useful for development of algorithms for solving the bilevel programming problems. We conclude that the deterministic user equilibrium link flows generally are directionally differentiable with respect to the perturbed parameters even if only travel demands are perturbed. This implies that the algorithm based on the sensitivity analysis for the bilevel transportation problem may not be defined well. Thirdly, by identifying the natures of some existing bilevel transportation problems with the network equilibrium constraint, we can design more efficient algorithms for these problems. For the standard continuous network design problem, a single level continuously differentiable optimization model in terms of link flows is proposed. This model results from the proof of the continuously differentiability of the marginal function defined for this special problem. Furthermore, the derivative information of this marginal function can be obtained by implementing a deterministic user equilibrium traffic assignment. Based on the derivative information, a convergent augmented Lagrangian method under certain conditions is designed to find a KKT (Karush-Kuhn-Tucker) point of the equivalent model and it is also available for the large-scale problem. (Abstract shortened by UMI.)
590 $a School code: 1223.
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650 4 $a Engineering, Civil. $3 783781
650 4 $a Engineering, System Science. $3 1018128
650 4 $a Transportation. $3 555912
650 4 $a Urban and Regional Planning. $3 1017841
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791 $a Ph.D.
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