**Reference:**

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.

**Abstract:**

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.

Corresponding technical report: pdf file (240 KB)

@inproceedings{vanDeS:07-009,

author={T.J.J. van den Boom and B. {D}e Schutter},

title={On a model predictive control algorithm for dynamic railway network management},

booktitle={Proceedings of the 2nd International Seminar on Railway Operations Modelling and Analysis (RailHannover2007)},

editor={I.A. Hansen and A. Radtke and J. Pachl and E. Wendler},

address={Hannover, Germany},

month=mar,

year={2007}

}

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