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

Authors :
S Stefano Fazi
Jing-Xin Dong
JC Jan Fransoo
Tom Van Woensel
Operations Planning Acc. & Control
EngD Data Science Support
EAISI Mobility
Research programme OPERA
Source :
Transportation Research. Part E: Logistics and Transportation Review, 142, Transportation Research. Part E: Logistics and Transportation Review, 142:102057. Elsevier, Transportation Research Part E: Logistics and Transportation Review, 142:102057. PERGAMON-ELSEVIER SCIENCE LTD
Publication Year :
2020

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.

Details

Language :
English
ISSN :
13665545
Volume :
142
Database :
OpenAIRE
Journal :
Transportation Research. Part E: Logistics and Transportation Review
Accession number :
edsair.doi.dedup.....5a06463e152fe9529b5a5fbe26a0671a
Full Text :
https://doi.org/10.1016/j.tre.2020.102057