蝴蝶优化算法研究综述

蝴蝶优化算法是一种新兴的元启发式算法，其思想来源于蝴蝶觅食和求偶的行为。为了进一步改善蝴蝶优化算法的搜索性能，加快对算法的研究与应用进程，综述了蝴蝶优化算法的原理与改进、与其他元启发式算法的对比及发展趋势。首先介绍了算法的基本模型；然后结合国内外文献，分类阐述了基于算法参数、基于混沌和量子优化、基于学习策略、基于种群多样性等方面的改进蝴蝶优化算法，同时，归纳总结了蝴蝶优化算法在图像处理、无线网络、粒子滤波、光伏系统、医疗系统等领域的应用；其次在优缺点和适用性等方面将其与其他元启发式算法进行了对比；最后对蝴蝶优化算法的未来研究发展方向进行了展望。

Literature Survey of Butterfly Optimization Algorithm

Butterfly optimization algorithm is a new metaheuristic algorithm, the idea of butterfly from foraging and courtship behavior. To further improve the search performance of butterfly optimization algorithm and speed up the research and application process of the algorithm, the principle, research status, comparison with other metaheuristic algorithms, and development trend of butterfly optimization algorithm are summarized. Firstly, the basic model of the algorithm is introduced. Then, combined with domestic and foreign literature, the variant algorithms are classified and described from the aspects of algorithm pa-rameters, chaos and quantum optimization, learning strategy, population diversity, and other improvement strategies. At the same time, the applications of butterfly optimization algorithm in the fields of image processing, wireless network, particle filter, photovoltaic system, medical system and other fields are classified. Next, the algorithm is compared with other metaheuristic algorithms in terms of advantages, disadvantages, and applicability. Finally, the future research and development direction of butterfly op-timization algorithm is prospected.