多策略改进的蜣螂优化算法及其工程实例应用  

Multi-strategy improved dung beetle optimization algorithm and its application in engineering examples

作　　者：朱国庆 韩东颖[2] 米振涛 刘艳飞 杜晓彤 Zhu Guoqing;Han Dongying;Mi Zhentao;Liu Yanfei;Du Xiaotong(China Academy of Machinery Seience&Technology Qingdao Branch Co.,Ltd.,Qingdao 266300,China;School of Vehicle and Energy,Yanshan University,Qinhuangdao 066004,China)

机构地区：[1]中国机械总院集团青岛分院有限公司,青岛266300 [2]燕山大学车辆与能源学院,秦皇岛066004

出　　处：《电子测量技术》2024年第21期82-99,共18页Electronic Measurement Technology

摘　　要：蜣螂优化算法(DBO)虽独具优势,同时也存在一些问题,如收敛精度低下以及容易陷入局部最优。为了解决这些难题,提出了一种名为MSIDBO的改进型蜣螂优化算法,目的是增强优化效果,同时保持全局和局部搜索的平衡。提出了一种自适应适应度距离平衡策略,该策略通过优化蜣螂的觅食和偷窃行为,有效地避免算法陷入局部最优解的困境;同时,引入引导学习策略和局部最优扰动方案,加快算法的收敛速度,平衡算法在局部开发和全局探索能力之间的关系。为评估MSIDBO算法的性能,采用CEC2017测试函数进行仿真实验,在3个实际工程设计问题中,同时运用了MSIDBO算法,并与其他5种优化算法进行了比较,结果表明,MSIDBO算法在收敛速度、求解精度和稳定性方面均表现出显著优势,充分验证了其在实际应用中的高效性和可靠性。Although the dung beetle optimization algorithm(DBO)has unique advantages,there are also some problems,such as low convergence accuracy and easy to fall into local optimum.In order to solve these problems,an improved dung beetle optimization algorithm named MSIDBO is proposed to enhance the optimization effect and maintain the balance between global and local search.An adaptive fitness distance balance strategy is proposed,which effectively avoids the dilemma of the algorithm falling into the local optimal solution by optimizing the foraging and stealing behavior of dung beetles.At the same time,the guided learning strategy and the local optimal perturbation scheme are introduced to accelerate the convergence speed of the algorithm and balance the relationship between the local development and global exploration ability of the algorithm.In order to evaluate the performance of MSIDBO algorithm,CEC2017 test function is used for simulation experiments.In three practical engineering design problems,MSIDBO algorithm is used at the same time,and compared with other five optimization algorithms.The results show that MSIDBO algorithm has significant advantages in convergence speed,solution accuracy and stability,which fully verifies its efficiency and reliability in practical application.

关 键 词：蜣螂优化算法 引导学习策略 自适应适应度距离平衡策略 局部最优扰动 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构] TN03[自动化与计算机技术—计算机科学与技术]