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Dynamic spatial price equilibrium, dynamic user equilibrium, and freight transportation in continuous time: A differential variational inequality perspective

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  • Friesz, Terry L.

Abstract

In this paper we provide a statement of dynamic spatial price equilibrium (DSPE) in continuous time as a basis for modeling freight flows in a network economy. The model presented describes a spatial price equilibrium due to its reliance on the notion that freight movements occur in response to differences between the local and distant prices of goods for which there is excess demand; moreover, local and distant delivered prices are equated at equilibrium. We propose and analyze a differential variational inequality (DVI) associated with dynamic spatial price equilibrium to study the Nash-like aggregate game at the heart of DSPE using the calculus of variations and optimal control theory. Our formulation explicitly considers inventory and the time lag between shipping and demand fulfillment. We stress that such a time lag cannot be readily accommodated in a discrete-time formulation. We provide an in-depth analysis of the DVI's necessary conditions that reveals the dynamic user equilibrium nature of freight flows obtained from the DVI, alongside the role played by freight transport in maintaining equilibrium commodity prices and the delivered-price-equals-local-price property of spatial price equilibrium. By intent, our contribution is wholly theoretical in nature, focusing on a mathematical statement of the defining equations and inequalities for dynamic spatial price equilibrium (DSPE), while also showing there is an associated differential variational inequality (DVI), any solution of which is a DSPE. The model of spatial price equilibrium we present integrates the theory of spatial price equilibrium in a dynamic setting with the path delay operator notion used in the theory of dynamic user equilibrium. It should be noted that the path delay operator used herein is based on LWR theory and fully vetted in the published dynamic user equilibrium literature. This integration is new and constitutes a significant addition to the spatial price equilibrium and freight network equilibrium modeling literatures. Among other things, it points the way for researchers interested in dynamic traffic assignment to become involved in dynamic freight modeling using the technical knowledge they already possess. In particular, it suggests that algorithms developed for dynamic user equilibrium may be adapted to the study of urban freight modelled as a dynamic spatial price equilibrium. As such, our work provides direction for future DSPE algorithmic research and application. However, no computational experiments are reported herein; instead, the computing of dynamic spatial price equilibria is the subject of a separate manuscript.

Suggested Citation

  • Friesz, Terry L., 2024. "Dynamic spatial price equilibrium, dynamic user equilibrium, and freight transportation in continuous time: A differential variational inequality perspective," Transportation Research Part B: Methodological, Elsevier, vol. 190(C).
  • Handle: RePEc:eee:transb:v:190:y:2024:i:c:s0191261524002091
    DOI: 10.1016/j.trb.2024.103085
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    References listed on IDEAS

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    1. Han, Ke & Piccoli, Benedetto & Friesz, Terry L., 2016. "Continuity of the path delay operator for dynamic network loading with spillback," Transportation Research Part B: Methodological, Elsevier, vol. 92(PB), pages 211-233.
    2. Friesz, Terry L. & Han, Ke, 2019. "The mathematical foundations of dynamic user equilibrium," Transportation Research Part B: Methodological, Elsevier, vol. 126(C), pages 309-328.
    3. Han, Ke & Friesz, Terry L. & Szeto, W.Y. & Liu, Hongcheng, 2015. "Elastic demand dynamic network user equilibrium: Formulation, existence and computation," Transportation Research Part B: Methodological, Elsevier, vol. 81(P1), pages 183-209.
    4. Chao, Gary S. & Friesz, Terry L., 1984. "Spatial price equilibrium sensitivity analysis," Transportation Research Part B: Methodological, Elsevier, vol. 18(6), pages 423-440, December.
    5. Terry L. Friesz, 2010. "Dynamic Optimization and Differential Games," International Series in Operations Research and Management Science, Springer, number 978-0-387-72778-3.
    6. Florian, Michael & Los, Marc, 1982. "A new look at static spatial price equilibrium models," Regional Science and Urban Economics, Elsevier, vol. 12(4), pages 579-597, November.
    7. José Holguín-Veras & Ning Xu & Miguel Jaller & John Mitchell, 2016. "A Dynamic Spatial Price Equilibrium Model of Integrated Urban Production-Transportation Operations Considering Freight Delivery Tours," Transportation Science, INFORMS, vol. 50(2), pages 489-519, May.
    8. Terry L. Friesz & David Bernstein & Tony E. Smith & Roger L. Tobin & B. W. Wie, 1993. "A Variational Inequality Formulation of the Dynamic Network User Equilibrium Problem," Operations Research, INFORMS, vol. 41(1), pages 179-191, February.
    9. Han, Ke & Friesz, Terry L. & Yao, Tao, 2013. "Existence of simultaneous route and departure choice dynamic user equilibrium," Transportation Research Part B: Methodological, Elsevier, vol. 53(C), pages 17-30.
    10. Han, Ke & Szeto, W.Y. & Friesz, Terry L., 2015. "Formulation, existence, and computation of boundedly rational dynamic user equilibrium with fixed or endogenous user tolerance," Transportation Research Part B: Methodological, Elsevier, vol. 79(C), pages 16-49.
    11. Friesz, Terry L. & Han, Ke & Bagherzadeh, Amir, 2021. "Convergence of fixed-point algorithms for elastic demand dynamic user equilibrium," Transportation Research Part B: Methodological, Elsevier, vol. 150(C), pages 336-352.
    12. Friesz, Terry L. & Rigdon, Matthew A. & Mookherjee, Reetabrata, 2006. "Differential variational inequalities and shipper dynamic oligopolistic network competition," Transportation Research Part B: Methodological, Elsevier, vol. 40(6), pages 480-503, July.
    13. Smith, Tony E. & Friesz, Terry L., 1985. "Spatial market equilibria with flow-dependent supply and demand : The single commodity case," Regional Science and Urban Economics, Elsevier, vol. 15(2), pages 181-218, June.
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