Grey Wolf Optimization

The Grey Wolf Optimization (GWO) algorithm was proposed by S. Mirjalili et al. in the paper Grey Wolf Optimizer. The paper proposed a novel algorithm based on the hunting and the hierarchy structure in grey wolves

Features

Enables the GWO algorithm to one of the provided 2D functions. The algorithm tries to find the global minimum of the selected function. Any of landscapes' 2D or nD functions can be selected.

The plot indicates the alpha, beta and delta wolves by the following colors:

• Alpha: green
• Beta: yellow
• Delta: brown

CLI

To print all available options execute:

swarm wolves -h

API

In addition to the cli you can also use the API:

from swarmlib import GWOProblem, FUNCTIONS

problem = GWOProblem(wolves=10, function=FUNCTIONS['michalewicz'])
best_wolf = problem.solve()
problem.replay()

Example