计算机应用研究2024，Vol.41Issue(1)：134-141,8.DOI:10.19734/j.issn.1001-3695.2023.05.0197
多策略融合的蛇优化算法及其应用
Multi-strategy fusion snake optimizer and its application
摘要
Abstract
This paper proposed a multi-strategy snake optimizer to address the problems of poor interactivity in the optimiza-tion-seeking phase of the snake algorithm,serious randomness of the initial population,and the tendency to fall into local opti-mal solutions.Firstly,it used an orthogonal matrix to initialize the snake population to make the individuals more uniformly dis-tributed;secondly,it designed an adaptive equation to explore the development phase switching to replace the original food quantity and temperature threshold to make the algorithm perform adaptive phase switching;finally,it used a joint reverse selec-tion strategy to replace the original new individual hatching method of the algorithm to improve the convergence accuracy of the algorithm while accelerating the convergence efficiency of the algorithm.It selected ten benchmark test functions to experiment the MSSO algorithm from different perspectives to test the algorithm performance,analyzed the effectiveness of each strategy,and used the Wilcoxon rank sum test to prove the algorithm significance,and verified the practicality of MSSO through two en-gineering application simulation experiments.The results of each experiment show that MSSO performs better than the compara-tive algorithm comprehensively,which proves that the MSSO algorithm improvement has improved in the aspects of the search ability,robustness and practicality.关键词
蛇优化算法/正交矩阵初始化/自适应阶段切换/联合反向选择/元启发算法/工程应用问题Key words
snake optimizer/orthogonal matrix initialization/adaptive phase switching/joint opposition selection/meta-heuristic algorithms/engineering application problems分类
信息技术与安全科学引用本文复制引用
王永贵,赵炀,邹赫宇,胡鹏程..多策略融合的蛇优化算法及其应用[J].计算机应用研究,2024,41(1):134-141,8.基金项目
国家自然科学基金面上项目(61772249) （61772249）
