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A globally convergent algorithm for transportation continuous network design problem

OPTIMIZATION AND ENGINEERING 2007年第3期8卷 241-257页

作者： Gao, Ziyou Sun, Huijun Zhang, Haozhi Beijing Jiaotong Univ Sch Traff & Transportat State Key Lab Rail Traff Control & Safety Beijing 100044 Peoples R China

The continuous network design problem (CNDP) is characterized by a bilevel programming model, in which the upper level problem is generally to minimize the total system cost under limited expenditure, while at the lower level the network users make choices with regard to route conditions following the user equilibrium principle. In this paper, the bilevel programming model for CNDP is transformed into a single level convex programming problem by virtue of an optimal-value function tool and the relationship between System Optimum ( SO) and User Equilibrium (UE). by exploring the inherent nature of the CNDP, the optimal-value function for the lower level user equilibrium problem is proved to be continuously differentiable and its derivative in link capacity enhancement can be obtained efficiently by implementing user equilibrium assignment subroutine. However, the reaction (or response) function between the upper and lower level problem is implicit and its gradient is difficult to obtain. Although, here we approximately express the gradient with the difference concept at each iteration, based on the method of successive averages (MSA), we propose a globally convergent algorithm to solve the single level convex programming problem. Comparing with widely used heuristic algorithms, such as sensitivity analysis based (SAb) method, the proposed algorithm needs not strong hypothesis conditions and complex computation for the inverse matrix. Finally, a numerical example is presented to compare the proposed method with some existing algorithms.

关键词： continuous network design problem b-level programming method of successive averages global convergence

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