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Coordinated routing system for fire detection by patrolling trucks with drones

无人机 巡逻 卡车 布线(电子设计自动化) 车辆路径问题 计算机科学 整数规划 运筹学 过程(计算) 运输工程 约束(计算机辅助设计) 工程类 计算机网络 地理 生物 机械工程 遗传学 操作系统 航空航天工程 考古 算法
作者
Maryam Momeni,Hamed Soleimani,Shahrooz Shahparvari,Behrouz Afshar-Nadjafi
出处
期刊:International journal of disaster risk reduction [Elsevier BV]
卷期号:73: 102859-102859 被引量:37
标识
DOI:10.1016/j.ijdrr.2022.102859
摘要

Vehicle routing problem with drones (VRPD) is an extension of classical vehicle routing, which involves the usage of trucks and drones. Nowadays, bushfires are taken into account as a major global challenging subject. Indeed, forests are very vulnerable to fires, and the classical patrol systems cannot patrol all areas of the forest and pastures due to the difficult crossing of some routes. The literature survey demonstrated that the mathematical models are an efficient approach for planning forest and rangeland patrols. Drones and trucks are used in cooperation for forest monitoring in this study, with drones acting as an efficient and accurate means of monitoring routes that are impassable to ground vehicles. However, this novel approach deals with several substantial challenges, including limitation in the drone's battery and the routing problem in an integrated truck-drone system based on considering hard-to-reach areas and creating a trade-off between time and cost of the patrol process. These issues make significant differences between the proposed novel approach and the classical vehicle routing problem. Thus, it is essential to develop a comprehensive approach to resolve these crucial issues. The present study develops a multi-objective mathematical programming model as mixed-integer programming for simultaneous patrolling of trucks and drones. The augmented epsilon constraint (AEC) method has been considered to solve the two-objective mathematical programming model. Besides, Benders' decomposition (BD) algorithm has been employed to evaluate the achieved results in large-size problems. The performance of the BD algorithm has been confirmed in this study. The findings indicated that the proposed model efficiently protected the forest via monitoring all areas, including impassable areas where ground patrolling is impossible (e.g., the lack of roads due to dense vegetation). Also, it was proved that this system was a novel, cost-effective patrol, which prevents uncontrollable fires in the shortest possible time.
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