| GAO Yaqiong(高亚琼),WU Jin,SU Zhengdong,LI Chaoxing.[J].高技术通讯(英文),2024,30(4):405~414 |
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| Research on multiple-strategy improved coati optimization algorithm for engineering applications |
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| DOI：10. 3772 / j. issn. 1006-6748. 2024. 04. 008 |
| 中文关键词: |
| 英文关键词: coati optimization algorithm (COA), chaotic map, multi-strategy |
| 基金项目: |
| Author Name | Affiliation | | GAO Yaqiong(高亚琼) | (School of Electronic Engineering, Xi’an University of Posts and Telecommunications, Xi’an 710121, P. R. China) | | WU Jin | | | SU Zhengdong | | | LI Chaoxing | |
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| 中文摘要: |
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| 英文摘要: |
| 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 initialize 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 comprehensive 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 application. 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. |
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