The rapid growth of online shopping and logistics have significantly raised the question of how to adequately meet customer delivery expectations. Considering the advancements made in drone technology, this challenge could be addressed more efficiently than using traditional vehicle-based delivery technologies. According to analysts, the use of aerial drones can be beneficial as they are capable of lowering the cost of transportation, avoiding stagnation on roads by flying over traffic congestion, and being non-polluting to nature by not consuming any fossil fuel. However, drone delivery optimization models are distinguished for their complexity, due to the nonlinear nature of the energy constraints. In this study, we analyze the computational complexity of the optimization model from [1, 2] and focus on the linearization of the energy consumption constraints, which are a nonlinear function of the payload and the travel time. We discuss and analyze various linearization techniques to reduce the resolution time especially for large data size problem instances.