An algorithm for freight train driver rescheduling in disruption situations

Abstract

Railway operators adjust timetables and reschedule rolling stock operation plans and crew duties accordingly when operations are disrupted. This paper discusses the problem of rescheduling driver assignment to freight trains after timetable adjustment has been completed. We model the problem as an integer programming problem with set-covering constraints, and solve it using the column generation technique. Numerical experiments using real data have revealed that the method can provide a quality driver-rescheduling plan within an acceptable computing time.