Real-Time Optimization of Energy Consumption in Railway Networks

In railway traffic, perturbations may give rise to conflicts, causing delays. As a countermeasure, effective re-scheduling and rerouting decisions can be taken by addressing the real-time Rail Traffic Management Problem (rtRTMP). One of its subproblems is the real-time Energy Consumption Minimization Problem (rtECMP). The latter enforces the train routing and precedences computed by a rtRTMP solver and defines train timings and speed profiles. The objective is to minimize the weighted sum of train energy consumption and total delay. In this paper, we propose an Ant Colony Optimization algorithm for the rtECMP and we test it on the French Pierrefitte-Gonesse control area with dense mixed traffic. The results show that, in a very short computing time, a remarkable exploration of the search space is performed before convergence.