The real-time railway traffic management problem consists of selecting appropriate train routes and schedules for minimizing the propagation of delay in case of traffic perturbation. In this paper, we tackle this problem by introducing RECIFE-MILP, a heuristic algorithm based on a mixed-integer linear programming model. RECIFE-MILP uses a model that extends one we previously proposed by including additional elements characterizing railway reality. In addition, it implements performance boosting methods selected among several ones through an algorithm configuration tool. We present a thorough experimental analysis that shows that the performances of RECIFE-MILP are better than the ones of the currently implemented traffic management strategy. RECIFE-MILP often finds the optimal solution to instances within the short computation time available in real-time applications. Moreover, RECIFE-MILP is robust to its configuration if an appropriate selection of the combination of boosting methods is performed.
RECIFE-MILP: An Effective MILP-Based Heuristic for the Real-Time Railway Traffic Management Problem
IEEE Transactions on Intelligent Transportation Systems ; 16 , 5 ; 2609-2619
01.10.2015
813263 byte
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
RECIFE-MILP: An Effective MILP-Based Heuristic for the Real-Time Railway Traffic Management Problem
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