Performance analysis of MILP based model predictive control algorithms for dynamic railway scheduling

In this paper we analyse the performance of solvers for Mixed Integer Linear Programming (MILP) problems that appear from the model predictive control of railway networks. Our aim is to study techniques that reduce the amount of delay using dynamic traffic management by the rescheduling of trains. Due to the size of the emerging MILP problem and the given constraints on solution time, a thorough analysis of different MILP solution techniques was necessary. It has been proven that a significant speedup in the solution time can be achieved by the proper restructuring of the matrices of the MILP problem. The simulation results also confirm the effectiveness of the proposed control technique and the ability of this setup to analyse the most delay-sensitive trains in the network.