Research on multiple-strategy improved coati optimization algorithm for engineering applications  

作　　者：GAO Yaqiong WU Jin SU Zhengdong LI Chaoxing 高亚琼(School of Electronic Engineering,Xi'an University of Posts and Telecommunications,Xi'an 710121,P.R.China)

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

出　　处：《High Technology Letters》2024年第4期405-414,共10页高技术通讯（英文版）

基　　金：Supported by the National Key R&D Program of China(2022ZD0119001).

摘　　要：In this paper,a multi-strategy improved coati optimization algorithm(MICOA)for engineering applications is proposed to improve the performance of the coati optimization algorithm(COA)in terms of convergence speed and convergence accuracy.First,a chaotic mapping is applied to initial-ize the population in order to improve the quality of the population and thus the convergence speed of the algorithm.Second,the prey’s position is improved during the prey-hunting phase.Then,the COA is combined with the particle swarm optimization(PSO)and the golden sine algorithm(Gold-SA),and the position is updated with probabilities to avoid local extremes.Finally,a population decreasing strategy is applied as a way to improve the performance of the algorithm in a comprehen-sive approach.The paper compares the proposed algorithm MICOA with 7 well-known meta-heuristic optimization algorithms and evaluates the algorithm in 23 test functions as well as engineering appli-cation.Experimental results show that the MICOA proposed in this paper has good effectiveness and superiority,and has a strong competitiveness compared with the comparison algorithms.

关 键 词：coati optimization algorithm(COA) chaotic map multi-strategy 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] O224[自动化与计算机技术—控制科学与工程]