Shipborne UAV deployment and search path optimization for long-range maritime search and rescue

Rapid response in long-range maritime search and rescue (SAR) remains challenging because search targets drift under environmental forcing, while search-and-rescue units (SRUs) operate under endurance limits and sea-state-affected mobility. Shipborne UAVs provide a promising sea–air capability, in which the mothership offers long-range persistence and the UAV provides rapid wide-area search. However, their operational benefit depends on the coordinated design of UAV release timing and search execution. This study develops a mission-level optimization framework for shipborne-UAV-assisted long-range SAR. The UAV release time, number of search attempts, and track-spacing sequence are jointly optimized to minimize the total response time and maximize a mission-level cumulative detection objective. Environmental effects are incorporated through a reduced-order drifting-target probability field and sea-state-induced SRU speed loss, enabling adaptive planning under time-varying marine conditions. The resulting bi-objective mixed-integer nonlinear optimization problem is solved using an improved particle swarm optimization algorithm. A scenario-based numerical case study using South China Sea environmental data demonstrates the proposed framework and reveals clear Pareto trade-offs between response time and the mission-level cumulative detection objective. The proposed framework further provides a transferable decision-support tool for mission-level sea–air SAR planning under drifting-target uncertainty and time-varying marine conditions.