Research on the scheduling model of flying defense team based on simulated annealing algorithm

Plant protection UAVs (unmanned aerial vehicles) are usually operated in the form of flying defense teams. At present, the scheduling organization of the flying defense teams is relatively extensive, resulting in the low efficiency of the flying defense teams. Reasonable scheduling of UAVs can improve the operational efficiency of the flying defense teams. By taking the rice smut prevention and control scenarios as the research object, according to the operation specifications of "single-spray triple-prevention" against rice smut, referring to the current situation of the order modes of flying defense operation, an order management and plant protection UAVs scheduling model is proposed in this study, to ensure the operation quality and operation efficiency of plant protection UAVs. The model has two parts: (1) Order management, which is an order sorting method that comprehensively considers order work area, time window, and order urgency; (2) Scheduling model, which is a UAV scheduling model based on simulated annealing algorithm. Taking 16 plots in Nanjing area in China and rice smut control tasks of 4 flying defense teams for case study, the simulated annealing algorithm and the greedy algorithm were used to make a comparative study on the time window lengths of 3-6 days. Research results showed that, when the operation time window length is 3-5 days, the longer the time window, the shorter the scheduling distance and waiting time, the longer the total operation time, and the higher the total revenue. When the time window length is 6 days, the total operation time and operation income will not change. This research can provide a scientific basis for the deployment and decision-making analysis of the UAVs flying defense teams, and provide a reference for the development of the intelligent scheduling system for agricultural machinery.