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A Successive Linear Optimization Approach to the Dynamic Traffic Assignment Problem

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  • James K. Ho

    (Brookhaven National Laboratory, Upton, New York)

Abstract

A dynamic model for the optimal control of traffic flow over a network is considered. The model, which treats congestion explicitly in the flow equations, gives rise to nonlinear, nonconvex mathematical programming problems. It has been shown for a piecewise linear version of this model that a global optimum is contained in the set of optimal solutions of a certain linear program. This paper presents a sufficient condition for optimality which implies that a global optimum can be obtained by successively optimizing at most N + 1 objective functions for the linear program, where N is the number of time periods in the planning horizon. Computational results are reported to indicate the efficiency of this approach.

Suggested Citation

  • James K. Ho, 1980. "A Successive Linear Optimization Approach to the Dynamic Traffic Assignment Problem," Transportation Science, INFORMS, vol. 14(4), pages 295-305, November.
    • Handle: RePEc:inm:ortrsc:v:14:y:1980:i:4:p:295-305
    DOI: 10.1287/trsc.14.4.295
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    Cited by:

    1. Zhu, Feng & Ukkusuri, Satish V., 2017. "Efficient and fair system states in dynamic transportation networks," Transportation Research Part B: Methodological, Elsevier, vol. 104(C), pages 272-289.
    2. Chou, Chang-Chi & Chiang, Wen-Chu & Chen, Albert Y., 2022. "Emergency medical response in mass casualty incidents considering the traffic congestions in proximity on-site and hospital delays," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 158(C).
    3. Anthony G O Yeh & P C Lai & S C Wong & Nelson H C Yung, 2004. "The Architecture for a Real-Time Traffic Multimedia Internet Geographic Information System," Environment and Planning B, , vol. 31(3), pages 349-366, June.
    4. Jiancheng Long & Wai Yuen Szeto, 2019. "Link-Based System Optimum Dynamic Traffic Assignment Problems in General Networks," Operations Research, INFORMS, vol. 67(1), pages 167-182, January.

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