Rescheduling Algorithm Using Operational
Patterns For Rolling Stock Operation At
Train Depots
Author(s)
T. Tomiyama, T. Sato, K. Okada & T. Wakamiya
Abstract
Railway companies have to create schedules for their rolling stock to operate a
large number of trains by defining which route each train runs on and when
maintenance is done. This scheduling task requires a lot of time and highlyskilled
operators, called rolling stock managers, because of numerous
complications. We developed an algorithm to help them that automatically
creates a schedule for rolling stock during disruptions. We applied the Dijkstra
method, which is a mathematical algorithm for searching efficient paths from a
network model like the routes taken by sales staff. Our algorithm takes into
consideration 1) maintenance cycles where railway companies are required by
law to periodically inspect the condition of all trains. It schedules maintenance to
continue these cycles. It also takes into account 2) operational patterns through
scheduling patterns to create schedules that can compete with manual schedules.
These patterns can represent experiences by rolling stock managers like the
rotations of train routes. We carried out numerical experiments using real data
(small and large numbers) at two train depots of a Japanese railway company.
The small ones included ten train sets and a bi-monthly schedule. The large ones
included 67 train sets and a monthly schedule. We generated experimental data
on virtual disruptions. Our algorithm could mostly generate feasible schedules
both from the small and large numbers of data, between 0.02 and 173.25 s, and
in 632.47 s. Slight deviations in maintenance cycles were involved in some of
the large ones. These results indicate that our algorithm could be feasible for real
situations, even though satisfaction with constraints and calculation time should
be improved to achieve highly interactive rescheduling operations.
Keywords: rolling stock operation, scheduling, Dijkstra method.
Keywords
rolling stock operation, scheduling, Dijkstra method
Related Book
Other papers in this volume
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