A UAV path planning method based on the framework of multi-objective jellyfish search algorithm.

Multi-constraint UAV path planning problems can be viewed as many-objective optimization problems that can be solved by meta-heuristic algorithms with good self-organizing optimization capabilities. However, such algorithms mostly use random initializing methods, resulting in low-quality initial paths that reduce the efficiency of subsequent algorithmic searches. Moreover, as the number of objective functions increases, meta-heuristic algorithms face inadequate selection pressure and convergence capability, which lead to poor solution.