Abstract
Abstract Flexible adaptation to the heterogeneous distribution of travel demand is a challenging issue in the transit network design and planning. Limited-stop service is a strategy used to deal with this problem. In this paper, a bi-level mathematical model is proposed in which the upper-level model minimizes the total fleet unused capacity of limited-stop services, while the objective function of the lower-level model is to minimize total expected travel time for all passengers. Since this model is operator-oriented, some constraints are embedded in it in order to prevent excessive fall of the passengers' service level. Actually, the upper level is a mixed integer linear programming model; but because of NP-hardness and the lower level model, a heuristic algorithm is developed in order to solve the proposed bi-level model. It's worth mentioning that this heuristic approach is based on iterated local search, simulated annealing, and tabu search metaheuristics. Finally, a vast variety of numerical experiments are carried out that are based on some virtual origin-destination demand matrices generated according to different characteristics. Computational results show that by replacing the local service with the set of limited-stop services, the fleet unused capacity can be reduced by up to 48%.
Published Version
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