Collaborative optimization of launch site selection and routing for UAV delivery under wind effects

Wind affects both energy consumption and routing decisions in UAV delivery, making launch site selection and route planning strongly interdependent. This paper investigates their joint optimization under wind effects. Under a quasi-steady two-dimensional uniform wind-field assumption, wind speed, wind direction, payload status, battery capacity, and time windows are incorporated into the problem. A mixed-integer linear programing model is developed to minimize total system energy consumption by jointly determining launch site selection, task assignment, and flight routes. To solve the problem efficiently, an adaptive large neighborhood search (ALNS) algorithm is proposed. For 9-node and 20-node instances, ALNS obtains the same results as Gurobi. For the 50-node instance, it finds a feasible solution in about 105 s. Results further show that wind conditions influence energy consumption, delivery time, route structure, and launch site choice. These findings support the joint optimization of launch site selection and routing in UAV delivery.