Augmented Lagrangian relaxation-based coordinated approach for global synchromodal transport planning with multiple operators

Wenjing Guo, Yimeng Zhang, Wenfeng Li, Rudy R. Negenborn and Bilge Atasoy

Transportation Research Part E: Logistics and Transportation Review, 2024, vol. 185, issue C

Abstract: Global synchromodal transportation is a promising strategy for providing efficient, reliable, flexible, and sustainable container shipping services across continents. It involves integrating multiple modes and routes owned by various operators to create a comprehensive transport plan. However, these operators often have their own local networks and are hesitant to cede control to a centralized platform. Instead, they prefer to share limited information in a coordinated manner to achieve a common goal without sacrificing their own benefits. This paper proposes a coordinated mechanism for global synchromodal transport planning, in which a global operator proposes incentives to local operators to select the most efficient modes and routes for shipping containers from one continent to another. An augmented Lagrangian relaxation approach is developed for the global operator to generate incentives, and a heuristic algorithm is designed to address the computational complexity of the optimization problems faced by local operators. We incorporate the proposed approaches with a rolling horizon framework to handle dynamic shipment requests received from spot markets and with a buffer strategy to address travel time uncertainties. The coordinated mechanism is tested on a real network between Asia and Europe, and results show that it can significantly increase total profits, reduce request rejections, and reduce infeasible transshipments compared to decentralized global transportation plans currently in use, particularly under scenarios with higher degrees of dynamism and uncertainty.

Keywords: Global synchromodal transport systems; Multiple operators; Coordinated mechanism; Augmented Lagrangian relaxation approach; Heuristic algorithm (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1016/j.tre.2024.103535

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