用对数函数描述收敛因子的改进灰狼优化算法及其应用  

Improved grey wolf optimization algorithm with logarithm function describing convergence factor and its application

作　　者：伍铁斌[1,2] 桂卫华 阳春华[1] 龙文[3] 李勇刚[1] 朱红求[1] WU Tiebin;GUI Weihua;YANG Chunhua;LONG Wen;LI Yonggang;ZHU Hongqiu(School of Information Science and Engineering,Central South University,Changsha 410083,China;College of Energy and Electrical Engineering,Hunan University of Humanities,Science and Technology,Loudi 417000,China;Key Laboratory of Economics System Simulation,Guizhou University of Finance and Economics,Guiyang 550025,China)

机构地区：[1]中南大学信息科学与工程学院,湖南长沙410083 [2]湖南人文科技学院能源与机电工程学院,湖南娄底417000 [3]贵州财经大学贵州省经济系统仿真重点实验室,贵州贵阳550025

出　　处：《中南大学学报（自然科学版）》2018年第4期857-864,共8页Journal of Central South University:Science and Technology

基　　金：国家自然科学基金资助项目(61621062;61463009;61673400);湖南省自然科学基金青年基金资助项目(2016JJ3079);贵州省科学技术基金资助项目(黔科合基础[2016]1022);娄底市科技计划项目(2017)~~

摘　　要：针对灰狼优化(grey wolf optimization,GWO)算法在求解复杂高维优化问题时存在解精度低、易陷入局部最优等缺点,提出一种基于对数函数描述收敛因子的改进GWO算法。采用佳点集方法初始化种群以保证个体尽可能均匀地分布在搜索空间中;提出一种基于对数函数描述的非线性收敛因子替代线性递减收敛因子,以协调算法的勘探和开采能力;对当前最优的3个个体执行改进的精英反向学习策略产生精英反向个体,以避免算法出现早熟收敛。研究结果表明改进算法具有较好的寻优性能。The grey wolf optimization(GWO)algorithm has a few disadvantages such as low precision and high possibility of being trapped in local optimum,an improved GWO algorithm was proposed for solving high-dimensional optimization problem based on the convergence factor about logarithmic function.An initial population was generated based on good point set method to assure that the individuals were distributed in the search space as uniformly as possible.A nonlinear convergence factor was proposed based on logarithm function to balance the exploration ability and exploitation ability.Improved elite opposition-based learning strategy was used to avoid premature convergence of GWO algorithm.Benchmark functions and parameters optimization of real application were employed to verify the performance of the improved GWO algorithm.The results show that the proposed algorithm has better performance.

关 键 词：灰狼优化算法 对数函数 收敛因子 

分 类 号：TP273.1[自动化与计算机技术—检测技术与自动化装置]