Atmospheric monitoring path optimization based on improved discrete cuckoo search algorithm

In this paper, we propose an improved discrete cuckoo search algorithm based on the spatial clustering for flight path optimization of atmospheric monitoring in industrial parks. This paper also optimizes the local operator and proposes the acceptance of the redesigned solution based on the Metropolis criterion to reduce the possibility of easily falling into local optimum. The standard TSPLIB library is selected for algorithm simulation and performance test in the analysis case, and the superiority of the algorithm is verified by comparing and analyzing with the standard discrete cuckoo search algorithm and particle swarm optimization algorithm. Finally, integration of improved trajectory optimization algorithms with the actual built UAV (Unmanned Aerial Vehicle) atmospheric monitoring platform, and the feasibility of the proposed flight path optimization algorithm is verified in an outdoor environment.