In an aerial package delivery scenario carried out by multiple Unmanned Aerial Vehicles (UAVs), it is important to maximize the collaboration and the resource sharing in the fleet and to satisfy, according to the UAVs' constraints, the largest possible portion of the tasks' requirements' space. In this thesis work, a UAVs-based parcel delivery problem is formulated and a Genetic Algorithm (GA) is proposed for solving the formulated task assignment problem for a fleet of heterogeneous UAVs. GAs are a class type of algorithms inspired by the known evolutionary mechanism of populations. The objective of the proposed task allocation method is to minimize the energy consumed by the fleet for executing the delivery tasks while respecting the time window delivery constraints and the maximum payload capacity of each UAV.