Feeder vessel routing and transshipment coordination at a congested hub port

Jian Gang Jin, Qiang Meng and Hai Wang

Transportation Research Part B: Methodological, 2021, vol. 151, issue C, 1-21

Abstract: With increasing container-shipping traffic, congestion at transshipment hub ports happens from time to time incurring longer-than-expected waiting time for vessels and loss of transshipment connections. This situation is even worse for feeder companies, due to their relatively lower berthing priority. It is essential to design the feeder vessel routes and schedules in response to hub port congestion while ensuring efficient transshipment connection with their connecting long-haul services. In this paper, we study the vessel routing and transshipment coordination problem for a feeder liner company where only limited choices of berthing time slots are available at the hub port. We proposed an arc-based mixed integer linear programming model and a set partitioning model with the objective of minimizing the total operating and transshipment connection cost. Two solution approaches are developed (1) a branch-&-price exact algorithm that can solve instances with up to 30 ports to optimality within reasonable computational time; and (2) a column generation heuristic method that yields high-quality near-optimal solutions very efficiently without having to implement a full-scale branch-&-bound search. Computational experiments based on a real-world shipping network and randomly generated test instances confirm the effectiveness and efficiency of the solution approaches. It is also demonstrated that, by integrating the hub port calling time decision with feeder vessel routing, transshipment coordination can be significantly enhanced even under hub port congestion situations.

Keywords: Maritime transport; Liner shipping; Feeder vessel; Routing; Port congestion; Column generation; Branch-&-price (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (8)

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DOI: 10.1016/j.trb.2021.07.002

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