This work proposes a new meta-heuristic called Grey Wolf Optimizer (GWO) inspired by grey
wolves (Canis lupus). The GWO algorithm mimics the leadership hierarchy and hunting
mechanism of grey wolves in nature. Four types of grey wolves such as alpha, beta, delta,
and omega are employed for simulating the leadership hierarchy. In addition, the three main
steps of hunting, searching for prey, encircling prey, and attacking prey, are implemented.
The algorithm is then benchmarked on 29 well-known test functions, and the results are …