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- Publisher Website: 10.1016/j.tre.2023.103118
- Scopus: eid_2-s2.0-85154044906
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Article: Stochastic service network design: The value of fixed routes
Title | Stochastic service network design: The value of fixed routes |
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Authors | |
Keywords | Column generation Fixed routes Multiple scenario approach Stochastic service network design |
Issue Date | 2023 |
Citation | Transportation Research Part E: Logistics and Transportation Review, 2023, v. 174, article no. 103118 How to Cite? |
Abstract | This study introduces a challenging service network design problem with stochastic demands and fixed routes. In this problem, the routes of some service vehicles are fixed during the whole planning horizon, while the remaining vehicles are flexible in that their routes can adapt to different realizations of customer demands each day. The problem is to determine which vehicles should be set as fixed and how their fixed routes should be designed. To solve this problem, we formulate a two-stage stochastic mixed-integer linear program. The fixed routes are designed in the first stage before customer demands are realized, and the routes for flexible vehicles are designed in the second stage after customer demands are observed. A learning-based multiple scenario approach is developed as the solution method. Numerical experiments on real-world operational data from a logistics company show that fixing the routes of some service vehicles may reduce the operational cost by an average of approximately 6.37% compared with that in the case of no fixed routes. |
Persistent Identifier | http://hdl.handle.net/10722/328861 |
ISSN | 2023 Impact Factor: 8.3 2023 SCImago Journal Rankings: 2.884 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Liu, Chuanju | - |
dc.contributor.author | Lin, Shaochong | - |
dc.contributor.author | Shen, Zuo Jun Max | - |
dc.contributor.author | Zhang, Junlong | - |
dc.date.accessioned | 2023-07-22T06:24:43Z | - |
dc.date.available | 2023-07-22T06:24:43Z | - |
dc.date.issued | 2023 | - |
dc.identifier.citation | Transportation Research Part E: Logistics and Transportation Review, 2023, v. 174, article no. 103118 | - |
dc.identifier.issn | 1366-5545 | - |
dc.identifier.uri | http://hdl.handle.net/10722/328861 | - |
dc.description.abstract | This study introduces a challenging service network design problem with stochastic demands and fixed routes. In this problem, the routes of some service vehicles are fixed during the whole planning horizon, while the remaining vehicles are flexible in that their routes can adapt to different realizations of customer demands each day. The problem is to determine which vehicles should be set as fixed and how their fixed routes should be designed. To solve this problem, we formulate a two-stage stochastic mixed-integer linear program. The fixed routes are designed in the first stage before customer demands are realized, and the routes for flexible vehicles are designed in the second stage after customer demands are observed. A learning-based multiple scenario approach is developed as the solution method. Numerical experiments on real-world operational data from a logistics company show that fixing the routes of some service vehicles may reduce the operational cost by an average of approximately 6.37% compared with that in the case of no fixed routes. | - |
dc.language | eng | - |
dc.relation.ispartof | Transportation Research Part E: Logistics and Transportation Review | - |
dc.subject | Column generation | - |
dc.subject | Fixed routes | - |
dc.subject | Multiple scenario approach | - |
dc.subject | Stochastic service network design | - |
dc.title | Stochastic service network design: The value of fixed routes | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1016/j.tre.2023.103118 | - |
dc.identifier.scopus | eid_2-s2.0-85154044906 | - |
dc.identifier.volume | 174 | - |
dc.identifier.spage | article no. 103118 | - |
dc.identifier.epage | article no. 103118 | - |
dc.identifier.isi | WOS:001017587800001 | - |