This paper discusses a heuristic approach for Team Orienteering Problems with Time Windows. The method we propose takes advantage of a solution model based on a hierarchic generalization of the original problem, which is combined with an Ant Colony System algorithm.Computational results on benchmark instances previously adopted in the literature suggest that the algorithm we propose is effective in practice.

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In this paper we present the results of a simulation study aimed at assessing an on-demand transportation system. The on-demand system uses minibuses that have neither fixed itineraries nor fixed stops. The minibuses are dynamically routed to accommodate the requests received by the users. To use the on-demand service, users communicate, close to their desired departure time, the origin and destination of the trip. They accept the service if the estimated arrival time at destination fulfills their service level threshold. In the simulation users may decide whether to walk, to use a standard bus, to call the on-demand service, and, if none of these options is satisfactory, to use a private car. We consider different scenarios to assess the potential benefits of the introduction of an on-demand service. We also analyze the scalability and responsiveness of the service. The results suggest that an on-demand system may be able to satisfy a large portion of user transportation requests and may be put beside standard transportation systems in order to provide a better transportation service to the users and substantially reduce the use of private cars.