Decision support scheduling for marintime search and rescue planning with a system of UAVs and fuel service stations

Abstract

When maritime accidents occur, search and rescue (SAR) operations for survivors are a top priority. To conduct the SAR, a fleet of Unmanned Aerial Vehicles (UAVs) can be used. The objective of the search task is to maximize the probability of locating targets. The goal of the rescue task is to follow survivors, transmit their location and status to the command center, and await the rescue team. In maritime SAR, the priority of a survivor being in a particular location changes with time due to current and wind. For persistent SAR operations with a system of UAVs, it is beneficial to simultaneously orchestrate the activities of multiple UAVs and fuel service stations. To address these problems, we develop a mixed integer linear program (MILP) capable of generating efficient search and rescue operation plans. For real time operations that account for unanticipated changes to the system parameters, a rolling horizon scheduling approach may be used. The MILP model is functionally capable of incorporation in such a system.