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Drones are currently seen as a viable way for improving the distribution ofparcels in urban and rural environments, while working in coordination withtraditional vehicles like trucks. In this paper we consider the parallel dronescheduling vehicle routing problem, where the service of a set of customersrequiring a delivery is split between a fleet of trucks and a fleet of drones.We consider two variations of the problem. In the first one the problem is moretheoretical, and the target is the minimization of the time required tocomplete the service and have all the vehicles back to the depot. In the secondvariant more realistic constraints involving operating costs, capacitylimitation and workload balance, are considered, and the target is to minimizethe total operational costs. We propose several constraint programming modelsto deal with the two problems. An experimental champaign on the instancespreviously adopted in the literature is presented to validate the new solvingmethods. The results show that on top of being a viable way to solve problemsto optimality, the models can also be used to derive effective heuristicsolutions and high-quality lower bounds for the optimal cost, if the executionis interrupted after its natural end.

Constraint Programming models for the parallel drone scheduling vehicle routing problem