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Communication Dans Un Congrès Année : 2021

Ant Colony Optimization for Energy-Efficient Train Operations

Résumé

Traffic perturbations in railway systems may give rise to conflicts, which cause delays w.r.t. the timetable. Dealing with them requires solving the real-time Rail Traffic Management Problem (rtRTMP). A subproblem of the rtRTMP is the real-time Energy Consumption Minimization Problem (rtECMP). It defines the speed profiles along with the timing of multiple trains in a given network and time horizon. It takes as input the train routing and precedences computed by a rtRTMP solver and its 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 30 seconds, a remarkable exploration of the search space is performed before convergence.
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Dates et versions

hal-03288839 , version 1 (16-07-2021)

Identifiants

Citer

Federico Naldini, Paola Pellegrini, Joaquin Rodriguez. Ant Colony Optimization for Energy-Efficient Train Operations. GECCO 2021, Genetic and Evolutionary Computation Conference Companion, Jul 2021, Lille, France. pp75-76, ⟨10.1145/3449726.3459436⟩. ⟨hal-03288839⟩
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