Using a general-purpose Mixed-Integer Linear Programming solver for the practical solution of real-time train rescheduling

In the present paper we develop a simple approach based on Mixed-Integer Linear Programming (MILP) techniques, which uses an ad-hoc heuristic preprocessing on the top of a general-purpose commercial solver applied to a standard event-based MILP formulation. A computational analysis on real cases shows that our approach can be successfully used for practical real-time train rescheduling, as it is able to deliver (almost) optimal solutions within the very tight time limits imposed by the real-time environment.