Uav track planning based on Chaotic Golden Jackal Optimization algorithm
Ran Ren, Hongfang Lv, Yi-Hao Jiang · 2023
The Golden jackal optimization (GJO) algorithm sometimes converges slowly and is easy to enter local optimization, a Chaos Golden Jackal Optimization (CGJO) algorithm is proposed. The population is disturbed by adding Tent chaos and Gaussian variation; Compare the performance of CGJO algorithm with GJO, PSO, and GWO algorithms, and analyze that CGJO has a faster convergence speed than GWO, PSOandGJO. Apply the four algorithms to drone trajectory planning, and it is found that the average path length of CGJO planning is much shorter than that of GWO, PSOand GJO.