T.J.J. van den Boom and B. De Schutter, "On a model predictive control algorithm for dynamic railway network management," Proceedings of the 2nd International Seminar on Railway Operations Modelling and Analysis (RailHannover2007) (I.A. Hansen, A. Radtke, J. Pachl, and E. Wendler, eds.), Hannover, Germany, 15 pp., Mar. 2007.
In this paper we discuss a model predictive control method for dynamic traffic management of railway networks. The main aim of the predictive controller is to recover from delays in an optimal way by breaking connections and changing the departure of trains (at a cost). To model the railway system we use a switching max-plus-linear system description. We define the model predictive control design problem for the railway network, and we show that the problem can be recast into a mixed integer linear programming problem. This problem can be solved using existing solvers for MILP problems, or with a genetic algorithm or tabu search algorithm. We also apply the control strategy to a model of the Dutch railway network.