Nowadays, the design of optimization algorithms is very popular to solve problems in various scientific fields. The optimization algorithms usually inspired by the natural behaviour of an agent, which can be humans, animals, plants, or a physical or chemical agent. Most of the algorithms proposed in the last decade inspired by animal behaviour. In this article, we present a new optimizer algorithm called the wild horse optimizer (WHO), which is inspired by the social life behaviour of wild horses. Horses usually live in groups that include a stallion and several mares and foals. Horses exhibit many behaviours, such as grazing, chasing, dominating, leading, and mating. A fascinating behaviour that distinguishes horses from other animals is the decency of horses. Horse decency behaviour is such that the foals of the horse leave the group before reaching puberty and join other groups. This departure is to prevent the father from mating with the daughter or siblings. The main inspiration for the proposed algorithm is the decency behaviour of the horse. The proposed algorithm was tested on several sets of test functions such as CEC2017 and CEC2019 and compared with popular and new optimization methods. The results showed that the proposed algorithm presented very competitive results compared to other algorithms. The source code is currently available for public from: https://www.mathworks.com/matlabcentral/fileexchange/90787-wild-horse-optimizer.

如今，优化算法的设计非常流行来解决各个科学领域的问题。优化算法通常受代理的自然行为启发，代理可以是人类、动物、植物或物理或化学代理。过去十年中提出的大多数算法都受到动物行为的启发。在本文中，我们提出了一种新的优化器算法，称为野马优化器（WHO），其灵感来自野马的社交生活行为。马通常群居，其中包括一匹种马和几匹母马和小马驹。马表现出许多行为，例如放牧、追逐、支配、领导和交配。将马与其他动物区分开来的迷人行为是马的体面。马的体面行为是这样的，马的小马驹在进入青春期之前离开群体并加入其他群体。这种离开是为了防止父亲与女儿或兄弟姐妹交配。所提出算法的主要灵感是马的体面行为。所提出的算法在CEC2017和CEC2019等多组测试函数上进行了测试，并与流行的和新的优化方法进行了比较。结果表明，与其他算法相比，所提出的算法呈现出非常有竞争力的结果。源代码目前可从以下网址公开：https://www.mathworks.com/matlabcentral/fileexchange/90787-wild-horse-optimizer。所提出算法的主要灵感是马的体面行为。所提出的算法在CEC2017和CEC2019等多组测试函数上进行了测试，并与流行的和新的优化方法进行了比较。结果表明，与其他算法相比，所提出的算法呈现出非常有竞争力的结果。源代码目前可从以下网址公开：https://www.mathworks.com/matlabcentral/fileexchange/90787-wild-horse-optimizer。所提出算法的主要灵感是马的体面行为。所提出的算法在CEC2017和CEC2019等多组测试函数上进行了测试，并与流行的和新的优化方法进行了比较。结果表明，与其他算法相比，所提出的算法呈现出非常有竞争力的结果。源代码目前可从以下网址公开：https://www.mathworks.com/matlabcentral/fileexchange/90787-wild-horse-optimizer。