In this article, we are interested in the dynamic management of a vehicles fleet, dedicated to the pick-up and/or delivery of parcels in a customers set. In order to have a more realistic model, travel times and time windows are subject to variations: we will present a realistic vehicle routing problem model obtained by introducing uncertainties data (flexible time windows and fuzzy travel times) modelled by using fuzzy logic. In the last, we will present a resolution preliminary results obtained by two approaches (heuristic insertion and genetic algorithm).

The current transport systems have to provide a given level of service to the final customer. Dynamic piloting models, able to react quickly to the events must be designed to guarantee this level of service. In this article, we are interested in the dynamic management of a vehicles fleet, dedicated to the pick-up and/or delivery of parcels in a customers set. In order to have a more realistic model, travel times and time windows are subject to variations. We will present two indicators qualifying a vehicle. routing service level in such situation. They allow the decision maker to realize a compromise between service quality and risk taking. These indicators will be then integrated in our platform, to solve the dynamic problem under uncertainties.