@Article{cmc.2024.050523,
AUTHOR = {Jian Zhao, Kang Wang, Jiacun Wang, Xiwang Guo, Liang Qi},
TITLE = {African Bison Optimization Algorithm: A New Bio-Inspired Optimizer with Engineering Applications},
JOURNAL = {Computers, Materials \& Continua},
VOLUME = {81},
YEAR = {2024},
NUMBER = {1},
PAGES = {603--623},
URL = {http://www.techscience.com/cmc/v81n1/58295},
ISSN = {1546-2226},
ABSTRACT = {This paper introduces the African Bison Optimization (ABO) algorithm, which is based on biological population. ABO is inspired by the survival behaviors of the African bison, including foraging, bathing, jousting, mating, and eliminating. The foraging behavior prompts the bison to seek a richer food source for survival. When bison find a food source, they stick around for a while by bathing behavior. The jousting behavior makes bison stand out in the population, then the winner gets the chance to produce offspring in the mating behavior. The eliminating behavior causes the old or injured bison to be weeded out from the herd, thus maintaining the excellent individuals. The above behaviors are translated into ABO by mathematical modeling. To assess the reliability and performance of ABO, it is evaluated on a diverse set of 23 benchmark functions and applied to solve five practical engineering problems with constraints. The findings from the simulation demonstrate that ABO exhibits superior and more competitive performance by effectively managing the trade-off between exploration and exploitation when compared with the other nine popular metaheuristics algorithms.},
DOI = {10.32604/cmc.2024.050523}
}