Using a general-purpose Mixed-Integer Linear Programming solver for the practical solution of real-time train rescheduling
•We propose an effective heuristic for real-time train rescheduling.•The heuristic uses a general-purpose Mixed-Integer Linear Programming solver.•Randomized variable fixing produces improved solutions for parallel runs.•The approach proved successful for real cases provided by an industrial company...
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| Vydáno v: | European journal of operational research Ročník 263; číslo 1; s. 258 - 264 |
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| Médium: | Journal Article |
| Jazyk: | angličtina |
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Elsevier B.V
16.11.2017
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| ISSN: | 0377-2217, 1872-6860 |
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| Abstract | •We propose an effective heuristic for real-time train rescheduling.•The heuristic uses a general-purpose Mixed-Integer Linear Programming solver.•Randomized variable fixing produces improved solutions for parallel runs.•The approach proved successful for real cases provided by an industrial company.
At a planning level, train scheduling consists of optimizing the routing and scheduling for a set of trains on a railway network. In real-time operations, however, the planned schedule constantly needs to be verified and possibly updated due to disruptions/delays that may require train rerouting or cancelation. In practice, an almost immediate reaction is required when unexpected events occur, meaning that trains must be rescheduled in a matter of seconds. This makes the time-consuming optimization tools successfully used in the planning phase completely inadequate, and ad-hoc (heuristic) algorithms have to be designed.
In the present paper we develop a simple approach based on Mixed-Integer Linear Programming (MILP) techniques, which uses an ad-hoc heuristic preprocessing on the top of a general-purpose commercial solver applied to a standard event-based MILP formulation. A computational analysis on real cases shows that our approach can be successfully used for practical real-time train rescheduling, as it is able to deliver (almost) optimal solutions within the very tight time limits imposed by the real-time environment. |
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| AbstractList | •We propose an effective heuristic for real-time train rescheduling.•The heuristic uses a general-purpose Mixed-Integer Linear Programming solver.•Randomized variable fixing produces improved solutions for parallel runs.•The approach proved successful for real cases provided by an industrial company.
At a planning level, train scheduling consists of optimizing the routing and scheduling for a set of trains on a railway network. In real-time operations, however, the planned schedule constantly needs to be verified and possibly updated due to disruptions/delays that may require train rerouting or cancelation. In practice, an almost immediate reaction is required when unexpected events occur, meaning that trains must be rescheduled in a matter of seconds. This makes the time-consuming optimization tools successfully used in the planning phase completely inadequate, and ad-hoc (heuristic) algorithms have to be designed.
In the present paper we develop a simple approach based on Mixed-Integer Linear Programming (MILP) techniques, which uses an ad-hoc heuristic preprocessing on the top of a general-purpose commercial solver applied to a standard event-based MILP formulation. A computational analysis on real cases shows that our approach can be successfully used for practical real-time train rescheduling, as it is able to deliver (almost) optimal solutions within the very tight time limits imposed by the real-time environment. |
| Author | Monaci, Michele Fischetti, Matteo |
| Author_xml | – sequence: 1 givenname: Matteo surname: Fischetti fullname: Fischetti, Matteo email: matteo.fischetti@unipd.it organization: DEI, Università di Padova, Via Gradenigo 6/A, Padova I-35131, Italy – sequence: 2 givenname: Michele surname: Monaci fullname: Monaci, Michele email: michele.monaci@unibo.it organization: DEI, Università di Bologna, Viale Risorgimento 2, Bologna I-40136, Italy |
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| Cites_doi | 10.1287/trsc.25.1.46 10.1287/opre.50.5.851.362 10.1109/TITS.2015.2446985 10.1016/j.trpro.2014.10.007 10.1287/trsc.2015.0605 10.1016/j.ejor.2006.10.034 10.1287/opre.2013.1231 10.1016/S0377-2217(01)00338-1 10.1007/s10589-016-9847-8 10.1016/j.trb.2009.05.004 10.1287/opre.17.6.941 10.1287/opre.2014.1327 10.1109/TITS.2015.2414294 10.1287/trsc.1080.0247 10.1287/opre.1080.0642 10.1016/j.trb.2014.01.009 |
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