A Flexible Transport Service for Passengers

Abstract The realization of innovative passengers transport services requires more and more often a greater flexibility and inexpensiveness of the service. To answer this request in many cases the physical solution is to realize a demand responsive transportation system (DRTS). A DRTS require the planning of travel paths (routing) and customers pick-up and drop-off times (scheduling) according to received requests, respecting the limited capacity of the fleet and time constraints (hard time windows) for each network's node, and the service time of the system. By the modelling point of view a DRTS can be effectively represented with a Dial-a-ride problem (DaRP). A DaRP derives from the Pick-up and Delivery Problem with Time Windows (PDPTW) and may operate according to a static or to a dynamic mode. In the static setting, all customers’ requests are known beforehand and the DaRP returns the vehicles routing and the passengers pick up and drop off time scheduling. The static setting may be representative of a phase of reservation occurred the day before the execution of the service. But, if the reservation requests must be processed on-line, even during the booking process there may be a certain level ad dynamism. In fact, if the algorithm works online, it manages each and every incoming request separately, and accepts or refuses it immediately, without knowing anything about the following. The operative program is constantly updated after each received request without refusal to carry out previous accepted services. In the dynamic mode, customers’ requests arrive when the service is already running and, consequently, the solution may change whilst the vehicle is already travelling. In this mode it is necessary that the schedule is updated when each new request arrives and that this is done in a short time to ensure that the potential customer will not leave the system before a possible answer. In this work, we describe a flexible people transport system capable of managing incoming transport demand in dynamic mode, using a solution architecture based on a two-stage algorithm to solve Dial-a-Ride Problem instances. In the first stage, a constructive heuristic algorithm quickly provides a feasible solution to accept the incoming demand. The algorithm in the second stage try to improve the solution evaluated at the first stage by using the time between two consecutive transportation events. The algorithm, unlike most of the works in the literature, use an objective function that optimizes the service punctuality.