Uzaktan iletişimin bulunduğu ortamda afet sonrası hasar tespiti için dron rotalama problemi

After a disaster event, obtaining fast and accurate information about the damaged built-in structure is crucial for planning life-saving search and rescue operations. This study focuses on determining drone routes for damage assessment in disaster-affected areas, aiming to maximize information gathering within a specified time frame while minimizing response time. Here, response time refers to the duration required for the collected data from a specific area to reach the operation center, where crucial decisions regarding disaster response are made. Drones can remotely transmit collected data from grids at recharge stations, allowing for quick assessment and route optimization. In order to construct the routes, we propose a path-based multi-objective mathematical model. However, since obtaining good quality solutions quickly is not possible for large instances with the mathematical model, we propose neighborhood search-based metaheuristics, namely, variable neighborhood descent, variable neighborhood search, and adaptive variable neighborhood search. The proposed methods consider grids' criticality levels, drones' limited battery capacity, and communication-related factors. In the multi-iteration setting that we consider, the transmitted information plays a crucial role in predicting damage levels of unvisited grids, influencing subsequent route construction by re-prioritizing these areas accordingly. The comprehensive numerical analysis compares algorithm performance under different settings and instances, demonstrating the potential of this approach in optimizing drone routing for effective disaster response operations.