불확실한 사건 발생을 고려한 UAV 활용 순찰-검사 경로 결정 문제

다국어 초록 (Multilingual Abstract)

Recently, increasing attention has been given to mobile surveillance systems using small Unmanned Aerial Vehicles (UAVs) to overcome the limitations of fixed-agent systems. This study addresses the problem of optimizing cooperative routing strategies for two types of UAV-based surveillance tasks: patrol and inspection. In the proposed framework, patrol UAVs explore a designated surveillance area to detect anomalies, while inspection UAVs conduct detailed investigations of regions identified as abnormal. To operate this system efficiently, we formulate a two-stage stochastic programming model that accounts for uncertainty in anomaly occurrence. In the first stage, optimal patrol routes are determined, and in the second stage, based on scenario-dependent realizations of anomalies, the routes for inspection UAVs are optimized. Given the NP-hard nature of the underlying routing problem, we propose a Progressive Hedging (PH) algorithm to enhance computational efficiency. Through numerical experiments, we demonstrate that the proposed method provides a feasible and effective solution for UAV patrol-inspection coordination under uncertainty.