Stochastic service network design with rerouting
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 qualit...
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| Format: | Article |
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Elsevier
2014
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| Online Access: | https://eprints.nottingham.ac.uk/49413/ |
| _version_ | 1848797990761791488 |
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| author | Bai, Ruibin Wallace, Stein W. Li, Jingpeng Chong, Alain Yee-Loong |
| author_facet | Bai, Ruibin Wallace, Stein W. Li, Jingpeng Chong, Alain Yee-Loong |
| author_sort | Bai, Ruibin |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-14T20:12:39Z |
| format | Article |
| id | nottingham-49413 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T20:12:39Z |
| publishDate | 2014 |
| publisher | Elsevier |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-494132020-05-04T16:42:37Z https://eprints.nottingham.ac.uk/49413/ Stochastic service network design with rerouting Bai, Ruibin Wallace, Stein W. Li, Jingpeng Chong, Alain Yee-Loong 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. Elsevier 2014-02-28 Article PeerReviewed Bai, Ruibin, Wallace, Stein W., Li, Jingpeng and Chong, Alain Yee-Loong (2014) Stochastic service network design with rerouting. Transportation Research Part B: Methodological, 60 . pp. 50-65. ISSN 0191-2615 service network design; stochastic programming; transportation logistics; rerouting https://www.sciencedirect.com/science/article/pii/S0191261513001999?via%3Dihub doi:10.1016/j.trb.2013.11.001 doi:10.1016/j.trb.2013.11.001 |
| spellingShingle | service network design; stochastic programming; transportation logistics; rerouting Bai, Ruibin Wallace, Stein W. Li, Jingpeng Chong, Alain Yee-Loong Stochastic service network design with rerouting |
| title | Stochastic service network design with rerouting |
| title_full | Stochastic service network design with rerouting |
| title_fullStr | Stochastic service network design with rerouting |
| title_full_unstemmed | Stochastic service network design with rerouting |
| title_short | Stochastic service network design with rerouting |
| title_sort | stochastic service network design with rerouting |
| topic | service network design; stochastic programming; transportation logistics; rerouting |
| url | https://eprints.nottingham.ac.uk/49413/ https://eprints.nottingham.ac.uk/49413/ https://eprints.nottingham.ac.uk/49413/ |