基于觅食能力分配搜索任务的侏儒猫鼬优化算法  

The Dwarf Mongoose Optimization Algorithm Based on Foraging Ability to Allocate Search Tasks

作　　者：张宁 王勇[1,2] 张伟 ZHANG Ning;WANG Yong;ZHANG Wei(College of Artificial Intelligence,Guangxi Minzu University,Nanning 530006,China;Guangxi Key Laboratory of Hybrid Computation&IC Design Analysis,Nanning 530006,China)

机构地区：[1]广西民族大学人工智能学院,广西南宁530006 [2]广西混杂计算与集成电路设计分析重点实验室,广西南宁530006

出　　处：《广西民族大学学报（自然科学版）》2023年第3期74-85,共12页Journal of Guangxi Minzu University ：Natural Science Edition

基　　金：国家自然科学基金资助项目(61662005);广西自然科学基金资助项目(2021GXNSFAA220068)。

摘　　要：针对侏儒猫鼬优化算法存在的不足,提出一种基于觅食能力分配搜索任务的侏儒猫鼬优化算法。首先采用tent混沌自适应步长平衡全局搜索与局部开发;针对alpha组搜索盲目性问题,优化其移动方向及移动能力;针对侦察组算法移动方向存在误导性问题,增强其个体纠错能力,从而提升个体觅食能力;改进保姆组移动算法,提升种群的局部开发能力;最后提出一种新的种群觅食策略,平衡各算法之间调用策略,提升算法整体性能。通过解决12个基准测试函数与支持向量机的参数优化问题,对该文算法性能进行数值实验验证。实验结果表明FADMO的全局收敛精度与全局收敛速度均有明显提高,并适用于实际问题求解。Aiming at the shortcomings of the Dwarf Mongoose Optimization Algorithm(DMO),a new improved Dwarf Mongoose Optimization Algorithm(FADMO)based on foraging ability allocation search tasks was proposed.First,the tent chaos adaptive step size is used to balance the global search and local development;to solve the blindness problem of the alpha group search,optimize its movement direction and movement ability;to solve the misleading problem of the movement direction of the reconnaissance group algorithm,enhance its individual error correction ability to improve Individual foraging ability;improving the babysitters group movement algorithm to enhance the local development ability of the population;finally,a new population foraging strategy is proposed,which balances the calling strategies between algorithms and improves the overall performance of the algorithm.By solving the parameter optimization problem of 12 benchmark functions and support vector machines,the performance of the algorithm in this paper is verified by numerical experiments.The experimental results show that the global convergence accuracy and global convergence speed of FADMO are significantly improved,and it is suitable for solving practical problems.

关 键 词：智能优化 侏儒猫鼬优化算法(DMO) 觅食能力分配任务 支持向量机参数优化 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]