A heuristic for real-time crew rescheduling during small disruptions

Thijs Verhaegh, Dennis Huisman (), Pieter-Jan Fioole and Juan Vera

No EI2016-09, Econometric Institute Research Papers from Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute

Abstract: Due to unforeseen problems, disruptions occur at railway passenger operators. Proper real-time crew management is needed to prevent disruptions to spread over space and time. Netherlands railways (NS) has algorithmic support from a solver to obtain good crew rescheduling solutions during big disruptions. However, small disruptions are still manually solved by human dispatchers who have limited solving capacity. In this paper the rescheduling for crews during small disruptions is modeled as an iterative-deepening depth-first search in a tree, which is combined with several OR techniques, obtaining a heuristic method. The heuristic focuses on real-life usability and uses the up- dated rolling-stock schedule as input. Testing the heuristic on about 5,000 test instances shows that the heuristic delivers good and desirable rescheduling solutions within fraction of seconds, outperforming other well-known methods from the literature.

Keywords: railways; real-time crew rescheduling (search for similar items in EconPapers)
Pages: 16
Date: 2016-02-23
New Economics Papers: this item is included in nep-cmp and nep-tre
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