Andrea D'Ariano

TL;DR: A branch and bound algorithm which includes implication rules enabling to speed up the computation of a train scheduling problem faced by railway infrastructure managers during real-time traffic control is developed.

TL;DR: A number of algorithmic improvements implemented in the real-time traffic management system ROMA (Railway traffic Optimization by Means of Alternative graphs), achieved by incorporating effective rescheduling algorithms and local rerouting strategies in a tabu search scheme are described.

TL;DR: The implementation of a real-time traffic management system, called ROMA (Railway traffic Optimization by Means of Alternative graphs), to support controllers in the everyday task of managing disturbances, making use of a branch-and-bound algorithm for sequencing train movements, while a local search algorithm is developed for rerouting optimization purposes.

TL;DR: An automated dispatching system provides better solutions in terms of delay minimization when compared to dispatching rules that can be adopted by a human traffic controller.

TL;DR: In this article, the authors propose an optimization model for railway traffic rescheduling based on a set of min-cost flow problems with activation constraints, and a lower bound is proposed.