Skip to main content

Research Repository

Advanced Search

Stochastic service network design with rerouting

Bai, Ruibin; Wallace, Stein W.; Li, Jingpeng; Chong, Alain Yee-Loong

Stochastic service network design with rerouting Thumbnail


Authors

Ruibin Bai

Stein W. Wallace

Jingpeng Li

Alain Yee-Loong Chong



Abstract

Service network design under uncertainty is fundamentally crucial for all freight transportation companies. The main challenge is to strike a balance between two conflicting objectives: low network setup costs and low expected operational costs. Together these have a significant impact on the quality of freight services. Increasing redundancy at crucial network links is a common way to improve network flexibility. However, in a highly uncertain environment, a single predefined network is unlikely to suit all possible future scenarios, unless it is prohibitively costly. Hence, rescheduling is often an effective alternative. In this paper, we proposed a new stochastic freight service network design model with vehicle rerouting options. The pro- posed model explicitly introduces a set of integer variables for vehicle rerouting in the second stage of the stochastic program. Although computationally more expensive, the resultant model provides more options (i.e. rerouting) and flexibility for planners to deal with uncertainties more effectively. The new model was tested on a set of instances adapted from the literature and its performance and characteristics are studied through both comparative studies and detailed analyses at the solution structure level. Implications for practical applications are discussed and further research directions are also provided.

Citation

Bai, R., Wallace, S. W., Li, J., & Chong, A. Y. (2014). Stochastic service network design with rerouting. Transportation Research Part B: Methodological, 60, https://doi.org/10.1016/j.trb.2013.11.001

Journal Article Type Article
Acceptance Date Nov 6, 2013
Online Publication Date Dec 23, 2013
Publication Date Feb 28, 2014
Deposit Date Jan 30, 2018
Publicly Available Date Mar 29, 2024
Journal Transportation Research Part B: Methodological
Print ISSN 0191-2615
Electronic ISSN 0191-2615
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 60
DOI https://doi.org/10.1016/j.trb.2013.11.001
Keywords service network design; stochastic programming; transportation logistics; rerouting
Public URL https://nottingham-repository.worktribe.com/output/722628
Publisher URL https://www.sciencedirect.com/science/article/pii/S0191261513001999?via%3Dihub

Files





Downloadable Citations