Ruibin Bai
A set-covering model for a bidirectional multi-shift full truckload vehicle routing problem
Bai, Ruibin; Xue, Ning; Chen, Jianjun; Roberts, Gethin Wyn
Authors
Ning Xue
Jianjun Chen
Gethin Wyn Roberts
Abstract
This paper introduces a bidirectional multi-shift full truckload transportation problem with operation dependent service times. The problem is different from the previous container transport problems and the existing approaches for container transport problems and vehicle routing pickup and delivery are either not suitable or inefficient. In this paper, a set covering model is developed for the problem based on a novel route representation and a container-flow mapping. It was demonstrated that the model can be applied to solve real-life, medium sized instances of the container transport problem at a large international port. A lower bound of the problem is also obtained by relaxing the time window constraints to the nearest shifts and transforming the problem into a service network design problem. Implications and managerial insights of the results by the lower bound results are also provided.
Citation
Bai, R., Xue, N., Chen, J., & Roberts, G. W. (in press). A set-covering model for a bidirectional multi-shift full truckload vehicle routing problem. Transportation Research Part B: Methodological, 79, https://doi.org/10.1016/j.trb.2015.06.002
Journal Article Type | Article |
---|---|
Acceptance Date | Jun 2, 2015 |
Online Publication Date | Jun 25, 2015 |
Deposit Date | Nov 3, 2017 |
Publicly Available Date | Nov 3, 2017 |
Journal | Transportation Research Part B: Methodological |
Print ISSN | 0191-2615 |
Electronic ISSN | 0191-2615 |
Publisher | Elsevier |
Peer Reviewed | Peer Reviewed |
Volume | 79 |
DOI | https://doi.org/10.1016/j.trb.2015.06.002 |
Keywords | Full truckload transport; Container transport; Vehicle routing; Set covering; Service network design |
Public URL | https://nottingham-repository.worktribe.com/output/753762 |
Publisher URL | http://www.sciencedirect.com/science/article/pii/S019126151500123X |
Contract Date | Nov 3, 2017 |
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