From the solitudinarian era to the present, the human race has been striving towards the betterment of his life by trying to find out the hidden secrets of our nature. Some time back one would hardly think that colonies of ant, pack of grey wolves, and elephants would be used to design an optimization algorithm. One of the optimization techniques called Grey Wolf Optimization (GWO) algorithm is motivated by the socio-hierarchical behaviour of the animal named Canis Lupus (Grey Wolf). In this paper, the detailed description of GWO is presented along with different development in standard GWO and its applications. Precisely, this article presents a state of the art review of the GWO algorithm, its progress, and applications in more complex real-world problem-solving.

从孤立主义时代到现在，人类一直在努力改善自己的生活，试图找出我们自然界的秘密。一段时间以前，人们几乎不会想到会使用蚁群，灰狼和大象来设计优化算法。一种名为灰狼优化（GWO）算法的优化技术是由名为Canis Lupus（灰狼）的动物的社会阶层行为所激发的。在本文中，将对GWO进行详细描述，并介绍标准GWO及其应用中的不同发展。准确地讲，本文介绍了GWO算法的最新技术，其进展以及在更复杂的实际问题解决中的应用。