A heuristic for real-time crew rescheduling during small disruptions
Document Type
Journal Article
Publication Date
2017
Subject Area
place - europe, mode - rail, technology - intelligent transport systems, operations - scheduling, planning - methods
Keywords
Crew rescheduling, Depth-first iterative-deepening, Heuristic, Railway optimization, Real-time rescheduling
Abstract
Due to unforeseen problems, disruptions occur in passenger railway operations. Proper real-time crew management is needed to prevent disruptions to spread over space and time. Netherlands Railways 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 inserting an uncovered task in a feasible set of duties. The problem is solved as an iterative-deepening depth-first search in a tree. To reduce computation time, we use several ideas to prune unpromising parts of the tree. We have tested the heuristic on about 5000 test instances obtained from real-world data. These tests show that the heuristic delivers good and desirable rescheduling solutions within at most 2 s.
Rights
Permission to publish the abstract has been given by SpringerLink, copyright remains with them.
Recommended Citation
Verhaegh, T., Huisman, D., Fioole, PJ., & Vera, J.C. (2017). A heuristic for real-time crew rescheduling during small disruptions. Public Transport, Vol. 9, pp. 325-342.
