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- Publisher Website: 10.1287/trsc.2018.0866
- Scopus: eid_2-s2.0-85077473485
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Article: Maintenance location routing for rolling stock under line and fleet planning uncertainty
Title | Maintenance location routing for rolling stock under line and fleet planning uncertainty |
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Authors | |
Keywords | Column-and-constraint generation Facility location Two-stage optimization Rolling stock Maintenance routing |
Issue Date | 2019 |
Citation | Transportation Science, 2019, v. 53, n. 5, p. 1252-1270 How to Cite? |
Abstract | © 2019 INFORMS. Rolling stock needs regular maintenance in a maintenance facility. Rolling stock from different fleets are routed tomaintenance facilities by interchanging the destinations of trains at common stations and by using empty drives. We consider the problem of locating maintenance facilities in a railway network under uncertain or changing line planning, fleet planning, and other uncertain factors. These uncertainties and changes are modeled by a discrete set of scenarios. We show that this new problem is NP-hard and provide a twostage stochastic programming and a two-stage robust optimization formulation. The secondstage decision is a maintenance routing problem with similarity to a minimum cost-flow problem.We prove that the facility location decisions remain unchanged under a simplified routing problem, and this gives rise to an efficient mixed-integer programming (MIP) formulation. This result also allows us to find an efficient decomposition algorithm for the robust formulation based on scenario addition (SA). Computational work shows that our improved MIP formulation can efficiently solve instances of industrial size. SA improves the computational time for the robust formulation even further and can handle larger instances due to more efficientmemory usage. Finally, we apply our algorithms on practical instances of the Netherlands Railways and give managerial insights. |
Persistent Identifier | http://hdl.handle.net/10722/296205 |
ISSN | 2023 Impact Factor: 4.4 2023 SCImago Journal Rankings: 2.475 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Tonissen, Denise D. | - |
dc.contributor.author | Arts, Joachim J. | - |
dc.contributor.author | Shen, Zuo Jun | - |
dc.date.accessioned | 2021-02-11T04:53:03Z | - |
dc.date.available | 2021-02-11T04:53:03Z | - |
dc.date.issued | 2019 | - |
dc.identifier.citation | Transportation Science, 2019, v. 53, n. 5, p. 1252-1270 | - |
dc.identifier.issn | 0041-1655 | - |
dc.identifier.uri | http://hdl.handle.net/10722/296205 | - |
dc.description.abstract | © 2019 INFORMS. Rolling stock needs regular maintenance in a maintenance facility. Rolling stock from different fleets are routed tomaintenance facilities by interchanging the destinations of trains at common stations and by using empty drives. We consider the problem of locating maintenance facilities in a railway network under uncertain or changing line planning, fleet planning, and other uncertain factors. These uncertainties and changes are modeled by a discrete set of scenarios. We show that this new problem is NP-hard and provide a twostage stochastic programming and a two-stage robust optimization formulation. The secondstage decision is a maintenance routing problem with similarity to a minimum cost-flow problem.We prove that the facility location decisions remain unchanged under a simplified routing problem, and this gives rise to an efficient mixed-integer programming (MIP) formulation. This result also allows us to find an efficient decomposition algorithm for the robust formulation based on scenario addition (SA). Computational work shows that our improved MIP formulation can efficiently solve instances of industrial size. SA improves the computational time for the robust formulation even further and can handle larger instances due to more efficientmemory usage. Finally, we apply our algorithms on practical instances of the Netherlands Railways and give managerial insights. | - |
dc.language | eng | - |
dc.relation.ispartof | Transportation Science | - |
dc.subject | Column-and-constraint generation | - |
dc.subject | Facility location | - |
dc.subject | Two-stage optimization | - |
dc.subject | Rolling stock | - |
dc.subject | Maintenance routing | - |
dc.title | Maintenance location routing for rolling stock under line and fleet planning uncertainty | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1287/trsc.2018.0866 | - |
dc.identifier.scopus | eid_2-s2.0-85077473485 | - |
dc.identifier.volume | 53 | - |
dc.identifier.issue | 5 | - |
dc.identifier.spage | 1252 | - |
dc.identifier.epage | 1270 | - |
dc.identifier.eissn | 1526-5447 | - |
dc.identifier.isi | WOS:000486399200003 | - |
dc.identifier.issnl | 0041-1655 | - |