Abstract Rolling stock optimization is a task that naturally arises by operating a railway system. It could be seen with different level of details. From a strategic perspective to have a rough plan which types of fleets to be bought to a more operational perspective to decide which coaches have to be maintained first. This paper presents a new approach to deal with rolling stock optimisation in case of a (long term) strike. Instead of constructing a completely new timetable for the strike period, we propose a mixed integer programming model that is able to choose appropriate trips from a given timetable to construct efficient tours of railway vehicles covering an optimized subset of trips, in terms of deadhead kilometers and importance of the trips. The decision which trip is preferred over the other is made by a simple evaluation method that is deduced from the network and trip defining data.
Timetable Sparsification by Rolling Stock Rotation Optimization
01.01.2018
6 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
Mixed integer programming , Railway rolling stock optimization , Operations research Business and Management , Operations Research/Decision Theory , Operations Research, Management Science , Operations Management , Big Data/Analytics , Engineering Economics, Organization, Logistics, Marketing , Game Theory
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