Stochastic service network design with rerouting

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

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.-L. (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: Jan 30, 2018
• 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
• Contract Date: Jan 30, 2018