Intelligent train scheduling on a high-loaded railway network

Authors:
Antonio Lova;Pilar Tormos;Federico Barber;Laura Ingolotti;Miguel A. Salido;Monsterrat Abril
Affiliations:
DEIOAC, Universidad Politecnica de Valencia, Spain;DEIOAC, Universidad Politecnica de Valencia, Spain;DSIC, Universidad Politecnica de Valencia, Spain;DSIC, Universidad Politecnica de Valencia, Spain;DSIC, Universidad Politecnica de Valencia, Spain;DSIC, Universidad Politecnica de Valencia, Spain
Venue:
ATMOS'04 Proceedings of the 4th international Dagstuhl, ATMOS conference on Algorithmic approaches for transportation modeling, optimization, and systems
Year:
2004

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Abstract

We present an interactive application to assist planners in adding new trains on a complex railway network. It includes many trains with different characteristics, whose timetables cannot be modified because they are already in circulation. The application builds the timetable for new trains linking the available time slots to trains to be scheduled. A very flexible interface allows the user to specify the parameters of the problem. The resulting problem is formulated as a CSP and efficiently solved. The solving method carries out the search assigning values to variables in a given order verifying the satisfaction of constraints where these are involved. When a constraint is not satisfied, a guided backtracking is done. Finally, the resulting timetable is delivered to the user who can interact with it, guaranteeing the traffic constraint satisfaction.