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

作　　者：吴亚中 陈璐 马强[1] 陈立正 WU Yazhong;CHEN Lu;MA Qiang;CHEN Lizheng(School of Civil&Hydraulic Engineering,Huazhong University of Science and Technology,Wuhan 430074,China;College of Water Conservancy and Civil Engineering,Xizang Agriculture and Animal Husbandry University,Linzhi,860000,Xizang China)

机构地区：[1]华中科技大学土木与水利工程学院,湖北武汉430074 [2]西藏农牧学院水利土木工程学院,西藏林芝860000

出　　处：《华中科技大学学报(自然科学版)》2025年第2期95-103,共9页Journal of Huazhong University of Science and Technology(Natural Science Edition)

基　　金：国家重点研发计划资助项目(2023YFC3081000);西藏自治区自然科学基金资助项目(XZ202401ZR0044)。

摘　　要：针对蜣螂优化算法易陷入局部极值、收敛速度慢等缺陷,提出了一种多策略增强的蜣螂优化算法.首先,创新地提出了基于最大最小欧式距离-Tent混沌映射种群初始化新方法,使初始种群均匀分布在解空间中,提升种群的多样性;进一步,引入黄金正弦搜索策略平衡算法全局探索和局部开发能力;最后,设计基于自适应t分布策略对全局最优解进行扰动,提升算法摆脱局部最优解的能力.将所提算法与4种经典元启发式算法和2种先进的改进算法在10个基准测试函数上进行寻优性能对比,通过Wilcoxon秩和检验结果分析了显著性差异水平,结果表明所提算法在高维单峰测试函数上均优于其他6种算法,在多峰测试函数上表现突出.此外,将所提算法应用在2个典型工程优化设计中,优化效果均达到最佳值,进一步验证了其在解决实际工程问题时的优越性.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 tdistribution 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-theart 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 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]