Ant Colony with Dynamic Local Search for the Time Scheduling of Transport Networks

Abstract

This article presents an ant colony optimization for the time scheduling of public transport traffic. In fact, the assistance of a decision support system becomes necessary for the real-time regulation of this transport networks since the size of the search space increases exponentially with the number of vehicles and stops. So, we propose an ant colony algorithm with dynamic local search, in the case of unpredictable disturbance. This approach consists in applying a local search window with increasing dimension according to the iterations. It treats the regulation problem as an optimization and provides the regulator with relevant decisions. A regulated timetable is proposed as solution aiming at minimizing the waiting time of passengers. We insure the three most important criteria of regulation which are the punctuality, the regularity and the correspondence.

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