| Citation: | TANG Andi, HAN Tong, XU Dengwu, et al. Chaotic multi-leader whale optimization algorithm[J]. Journal of Beijing University of Aeronautics and Astronautics, 2021, 47(7): 1481-1494. doi: 10.13700/j.bh.1001-5965.2020.0585(in Chinese)
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Aimed at the path planning problem of Unmanned Aerial Vehicle (UAV), a path planning method based on a Chaotic Multi-Leader Whale Optimization Algorithm (CML-WOA) is proposed. In the known flight environment, 3D model of flight area and a flight path cost model are established. By introducing penalty functions, the constrained 3D path planning problem is transformed into an unconstrained multi-dimensional function optimization problem, which is solved using CML-WOA to obtain the optimal flight path. To overcome the defect that the WOA is easy to fall into local optimum, this paper introduces the cubic mapping chaos operator to improve the initial population and enhance the population diversity. And the Sine Cosine Algorithm (SCA) is integrated through an adaptive framework. A multi-leader search strategy is used to effectively improve the algorithm exploitation and exploration capability. Finally, a greedy strategy is used to ensure the convergence efficiency. The proposed improved CML-WOA is tested and validated by 20 benchmark functions test and path planning simulation experiments. The results show that the algorithm has significantly improved performance compared to other algorithms, with strong local optimal avoidance capability, higher convergence accuracy and convergence speed. Also, it is able to provide stable and fast planning of safe and feasible flight path with minimum cost and satisfying constraints.
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