One of the most innovative solutions treated in the literature in order to reduce the environmental impact of urban parcel delivery logistics is the use of drones for delivery on the last kilometer. Consequently, nowadays, the primary challenge is essentially related to the drones’ fleet sizing according to its means of support for the urban delivery of parcels. In this paper, we will discuss the issue of dimensioning from a forecast of deliveries of an urban perimeter, the size of the fleet, the stock of battery to dispose of and the strategy of battery charging. We will present an analytical model expressing the proposed problem of the optimal drones’ delivery mission taking into account the issues of autonomy and energy consumption related to the drone’s technical specification. According to the developed analytical model, two optimization policies will be proposed. The first policy consists of planning missions under reducing distance. The second policy tries to make a compromise between the distance and the number of drones. A case study will be presented in order to compare the two policies based on the overall cost of a plan. The main objective of the study is to create a decision-making tool for the design of a drone fleet in the case of forecast deliveries over a time horizon under operational constraints.

In this article, the main subject is the problem of the location of Urban Distribution Centers (UDC) in an environment characterized by uncertainty. Thus, a decision support process based on fuzzy multi-criteria methods (F-MCDM) will be proposed as the solution. The CATWOE method is used for identifying the Stakeholders (PPs) concerned by the localization. Furthermore, direct interviews and the review of the literature help to enhance the decision criteria. The use of the F-SWARA method made it possible to weight the criteria by taking into consideration the opinion of the PPs. The F-ENTROPY method corrected the subjectivity of the weights given by the first method. The hybridization of the two is a first in the literature in this field and allows precise and realistic results. In the end, the different alternatives obtained by the F-VIKOR method are ranked. This approach was applied to the city of Casablanca, which is extremely impacted by the negative externalities of urban freight transport. The results of this study showed that zone four (AIN SBAA) is the best zone to implement the UDC in the city of Casablanca. The sensitivity analysis validated the robustness of the model.