Unmanned Aerial Vehicles (UAVs) are increasingly used in critical infrastructure maintenance due to their ability to improve safety, efficiency, and access in challenging environments. This paper focuses on optimizing drone-assisted equipment delivery for high-voltage power line maintenance, with the goal of minimizing the number of drones required to serve all pylons that lie on a line. Unlike prior work that maximizes delivery profit given a fixed fleet size, we aim to minimize the fleet size itself, addressing deployment constraints, such as load and energy, and coordination complexity. We introduce a new optimization problem, the Minimum Drone Delivery Problem (MDDP), and study three key variants: unitary loads (MDDP-U), arbitrary loads (MDDP-A), and non-overlapping missions (N-MDDP). We formulate MDDP as an Integer Linear Program and prove its \( NP \) -hardness. To solve it, we propose polynomial-time approximation algorithms and a heuristic. Extensive evaluations on synthetic datasets demonstrate the effectiveness and scalability of our approaches.