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Optimal Control of Oversaturated Store-and-Forward Transportation Networks

Author

Listed:
  • G. C. D'Ans

    (IBM, Armonk, New York)

  • D. C. Gazis

    (IBM, Armonk, New York)

Abstract

A general method is developed for the dynamic optimization of multi-commodity flows in an oversaturated, store-and-forward transportation network. The network is characterized by time-varying inputs, and the existence of queues in front of certain nodes where the incoming flows exceed the capacity to discharge them, during a certain period of oversaturation. The method consists of discretizing in time and solving a linear programming (LP) problem, in order to obtain the order of exhaustion of the various queues and an approximation to their, optimum time variation. The LP solution may be refined to any degree of desired accuracy, or used as a first step in a two-step procedure, where the order of exhaustion of the queues of the LP solution is used in a variational scheme to obtain the exact solution. The method is demonstrated by optimizing the operation of a two-node, four-queue network.

Suggested Citation

  • G. C. D'Ans & D. C. Gazis, 1976. "Optimal Control of Oversaturated Store-and-Forward Transportation Networks," Transportation Science, INFORMS, vol. 10(1), pages 1-19, February.
    • Handle: RePEc:inm:ortrsc:v:10:y:1976:i:1:p:1-19
    DOI: 10.1287/trsc.10.1.1
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    Cited by:

    1. Lee, Seunghyeon & Wong, S.C. & Varaiya, Pravin, 2017. "Group-based hierarchical adaptive traffic-signal control part I: Formulation," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 1-18.
    2. Chang, Tang-Hsien & Lin, Jen-Ting, 2000. "Optimal signal timing for an oversaturated intersection," Transportation Research Part B: Methodological, Elsevier, vol. 34(6), pages 471-491, August.
    3. Li, Pengfei & Mirchandani, Pitu & Zhou, Xuesong, 2015. "Solving simultaneous route guidance and traffic signal optimization problem using space-phase-time hypernetwork," Transportation Research Part B: Methodological, Elsevier, vol. 81(P1), pages 103-130.
    4. Recker, Will, 2008. "Development of an Adaptive Corridor Traffic Control Model," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt1sq7049f, Institute of Transportation Studies, UC Berkeley.
    5. Recker, Will & Zhenhg, Xing & Chu, Lianyu, 2010. "Development of an Adaptive Corridor Traffic Control Model," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt3tx5b17h, Institute of Transportation Studies, UC Berkeley.
    6. Yannis Pavlis & Will Recker, 2009. "A Mathematical Logic Approach for the Transformation of the Linear Conditional Piecewise Functions of Dispersion-and-Store and Cell Transmission Traffic Flow Models into Linear Mixed-Integer Form," Transportation Science, INFORMS, vol. 43(1), pages 98-116, February.
    7. Lee, Seunghyeon & Wong, S.C., 2017. "Group-based approach to predictive delay model based on incremental queue accumulations for adaptive traffic control systems," Transportation Research Part B: Methodological, Elsevier, vol. 98(C), pages 1-20.
    8. Wen-Long Jin, 2021. "A Link Queue Model of Network Traffic Flow," Transportation Science, INFORMS, vol. 55(2), pages 436-455, March.

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