In previous studies, almost all urban network design models/methods made attempts to optimize transportation system performance, such as minimizing road traffic congestion, by determining optimal road capacity expansion schemes, with the assumption of indestructible road infrastructure. However, road infrastructure definitely deteriorates over time, and needs periodic maintenance and repairs. This paper proposes a bilevel programming model for the urban freight transportation network design problem (UFTNDP) by taking into account the heterogeneity of road classifications and road damages from the perspective of road maintenance. The model aims to improve network performance as much as possible by determining an optimal joint scheme of road capacities and classifications. At the upper level, road planning aims to minimize total system cost by determining a joint optimal scheme of road capacities and road classifications. The lower level is a traffic assignment problem that characterizes network users’ path choice behavior. We then propose an improved system optimum (SO) relaxation–based method to solve the optimization model. Numerical examples validated the developed model and tested the computational efficiency of the proposed algorithm. Numerical results revealed that (1) the improved solution algorithm performs better, because it saves 97.3% of computational time compared with the original SO relaxation–based method; (2) the algorithm has the potential to be extended to solving a general discrete network design problem; and (3) a simultaneous optimization of road classification and capacity works better in improving system performance of an urban freight transportation network.


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    Title :

    Joint Optimization of Road Classification and Road Capacity for Urban Freight Transportation Networks


    Contributors:
    Ye, Yipeng (author) / Wang, Hua (author) / Zhang, Xiaoning (author) / Li, Rui (author)


    Publication date :

    2020-08-14




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown




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