Research on adaptive coati optimization algorithm based on chaos and perturbation strategies  

作　　者：Wu Jin Gao Yaqiong Su Zhengdong Xiong Hao 

机构地区：[1]School of Electronic Engineering,Xi'an University of Posts and Telecommunications,Xi'an 710121,China

出　　处：《The Journal of China Universities of Posts and Telecommunications》2024年第6期44-56,共13页中国邮电高校学报(英文版)

基　　金：supported by the National Key Research and Development (R&D) Program of China:Science and Technology Innovation 2030 (2022ZD0119000)。

摘　　要：The coati optimization algorithm(COA) is a bionic optimization algorithm that imitates natural phenomena and has good performance, but it suffers from the limitations of slow convergence and low accuracy of the optimal solution. Therefore, in this paper, an improved meta-heuristic algorithm called the adaptive sine coati optimization algorithm(ASCOA) is proposed. The proposed algorithm introduces a chaotic mechanism to optimize the initialized population. Cauchy perturbation and Levy flight are added in the exploitation phase to dynamically adjust the position updating method with probability to avoid falling into a locally optimal solution. And adaptive weights are added as a way to comprehensively improve the overall algorithmic optimality-seeking ability. The performance of ASCOA is tested in different dimensions using 13 sets of test functions, comparing ASCOA with well-known meta-heuristic algorithms through numerical results as well as convergence curves. ASCOA is also applied to engineering optimization. Simulation results show that the ASCOA can balance exploration and exploitation and improve the convergence speed and numerical accuracy. The Wilcoxon rank sum test shows that the results obtained in the paper are statistically significant.

关 键 词：chaotic maps Levy flight Cauchy perturbation adaptive strategy 

分 类 号：O17[理学—数学]