Collaborative ant colony algorithm for online regional bus scheduling

Abstract

An online regional bus scheduling model is proposed which focuses on the dynamic regulation of scheduling according to changes in the external environment, dynamic occurrences and periodic encounters of traffic incidents that interfere with the timely completion of vehicle trips. This paper employs fuzzy and random numbers to reflect uncertain delays as a result of meeting yard capacity constraints and other practical factors. A collaborative ant colony algorithm is employed to address the premature convergence defects of a traditional ant colony algorithm and to define the construct rules, pheromones, heuristic information and selection strategies of solutions. Finally, the validity of the proposed model and algorithm is verified by a numerical example.

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