A variant of the split vehicle routing problem with simultaneous deliveries and pickups for inland container shipping in dry-port based systems

Journal Article (2020)
Author(s)

S. Fazi (TU Delft - Transport and Logistics, Rijksuniversiteit Groningen)

Jan C. Fransoo (Hamburg University of Technology)

Tom Van Woensel (Eindhoven University of Technology)

Jing Xin Dong (Newcastle University)

Research Group
Transport and Logistics
Copyright
© 2020 S. Fazi, Jan C. Fransoo, Tom Van Woensel, Jing Xin Dong
DOI related publication
https://doi.org/10.1016/j.tre.2020.102057
More Info
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Publication Year
2020
Language
English
Copyright
© 2020 S. Fazi, Jan C. Fransoo, Tom Van Woensel, Jing Xin Dong
Research Group
Transport and Logistics
Volume number
142
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Abstract

In this paper, we will study a typical problem in inland container shipping, concerning the barge transportation of maritime containers between a dry port and a set of seaport terminals. The barges depart from the dry port and visit a set of sea terminals, where containers need either to be dropped off or picked up. The goal is to achieve economies of scale with barges and avoid trucking as much as possible. The decision thus involves finding the best allocation of containers to barges in order to guarantee on-time delivery and meet capacity restrictions. The problem will be modeled as a variant of the split vehicle routing problem with simultaneous pickups and deliveries coupled with time features. The model includes parameters that can be tuned to improve barge utilization and travelling distance. A hybrid local search meta-heuristic algorithm, combined with a branch-and-cut solver, will be developed to solve the model. Numerical experiments have been conducted to test the performance of the algorithm and provide solution analysis for practical insights. Real-world data has been collected from a local barge operator based in the Port of Rotterdam region and will be used as input for the experiments. This will result in an in-depth analysis into current planning practices. The proposed framework complements existing models in the literature and contributes to the development of a comprehensive set of decision support tools, which help in the decision-making process for inland terminals.