华中科技大学学报（自然科学版）2025，Vol.53Issue(2)：95-103,9.DOI:10.13245/j.hust.250185
多策略增强的蜣螂优化算法及其工程应用
Multi-strategy enhanced dung beetle optimizer algorithm and its engineering application
摘要
Abstract
A multi-strategy enhanced dung beetle optimizer algorithm was proposed to address the defects of the dung beetle optimizer algorithm such as easy to fall into local extremes and slow convergence.Firstly,a novel approach of population initialization based on maximum minimum Euclidean distance-Tent chaotic mapping was proposed to make the initial population uniformly distributed in the solution space to enhance population diversity.Furthermore,a golden sine search strategy was introduced to balance global exploration and local exploitation capabilities.Finally,a disturbance strategy based on adaptive t-distribution was designed to perturb the global optimal solution,enhancing the algorithm's ability to escape local optima.The optimization performance of the proposed algorithm was compared with four classical metaheuristic algorithms and two state-of-the-art improved dung beetle optimizer algorithms on 10 benchmark test functions,and the results show that the proposed algorithm outperforms six other algorithms on high-dimensional unimodal test functions and excels in multimodal test functions.The Wilcoxon rank-sum test was utilized to analyze the significance level of differences.In addition,the application of the proposed algorithm in two typical engineering optimization designs further validates its superiority in addressing real-world engineering problems.关键词
蜣螂优化算法/Tent混沌映射/黄金正弦搜索/自适应t分布策略/工程优化设计Key words
dung beetle optimizer algorithm/Tent chaotic mapping/golden sine search/adaptive t-distribution strategy/engineering optimization design分类
信息技术与安全科学引用本文复制引用
吴亚中,陈璐,马强,陈立正..多策略增强的蜣螂优化算法及其工程应用[J].华中科技大学学报（自然科学版）,2025,53(2):95-103,9.基金项目
国家重点研发计划资助项目(2023YFC3081000) （2023YFC3081000）
西藏自治区自然科学基金资助项目(XZ202401ZR0044). （XZ202401ZR0044）
