TY  - EJOU
AU  - Ye, Zhiwei 
AU  - Zhao, Tao 
AU  - Liu, Chun 
AU  - Zhang, Daode 
AU  - Bai, Wanfang 

TI  - An Improved Honey Badger Algorithm through Fusing Multi-Strategies
T2  - Computers, Materials \& Continua

PY  - 2023
VL  - 76
IS  - 2
SN  - 1546-2226

AB  - The Honey Badger Algorithm (HBA) is a novel meta-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-Whitney U 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: .
KW  - Honey Badger Algorithm; multi-strategies fusion; tent chaotic mapping; compound random factors

DO  - 10.32604/cmc.2023.038787