An Improved Honey Badger Algorithm through Fusing Multi-Strategies  

作　　者：Zhiwei Ye Tao Zhao Chun Liu Daode Zhang Wanfang Bai 

机构地区：[1]School of Computer Science,Hubei University of Technology,Wuhan,430068,China [2]Xining Big Data Service Administration,Xining,810000,China

出　　处：《Computers, Materials & Continua》2023年第8期1479-1495,共17页计算机、材料和连续体（英文）

基　　金：supported by National Science Foundation of China(Grant No.52075152);Xining Big Data Service Administration.

摘　　要：TheHoney Badger Algorithm(HBA)is a novelmeta-heuristic algorithm proposed recently inspired by the foraging behavior of honey badgers.The dynamic search behavior of honey badgers with sniffing and wandering is divided into exploration and exploitation in HBA,which has been applied in photovoltaic systems and optimization problems effectively.However,HBA tends to suffer from the local optimum and low convergence.To alleviate these challenges,an improved HBA(IHBA)through fusing multi-strategies is presented in the paper.It introduces Tent chaotic mapping and composite mutation factors to HBA,meanwhile,the random control parameter is improved,moreover,a diversified updating strategy of position is put forward to enhance the advantage between exploration and exploitation.IHBA is compared with 7 meta-heuristic algorithms in 10 benchmark functions and 5 engineering problems.The Wilcoxon Rank-sum Test,Friedman Test and Mann-WhitneyU Test are conducted after emulation.The results indicate the competitiveness and merits of the IHBA,which has better solution quality and convergence traits.The source code is currently available from:https://github.com/zhaotao789/IHBA.

关 键 词：Honey Badger Algorithm multi-strategies fusion tent chaotic mapping compound random factors 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]