optimizer_gwo: Grey Wolf Optimizer

In metANN: Metaheuristic and Gradient-Based Optimization for Neural Network Training and Continuous Problems

Grey Wolf Optimizer

Description

Creates a Grey Wolf Optimizer object for continuous optimization problems.

Usage

optimizer_gwo(pop_size = 30, max_iter = 100, a_start = 2, a_end = 0)

Arguments

pop_size	Population size.
max_iter	Maximum number of iterations.
a_start	Initial value of the control parameter a.
a_end	Final value of the control parameter a.

Value

An object of class "met_optimizer".

References

Mirjalili, S., Mirjalili, S. M., and Lewis, A. (2014). Grey Wolf Optimizer. Advances in Engineering Software, 69, 46–61. doi:10.1016/j.advengsoft.2013.12.007

Mirjalili, S. (2015). How Effective is the Grey Wolf Optimizer in Training Multi-Layer Perceptrons. Applied Intelligence, 43, 150–161. doi:10.1007/s10489-014-0645-7

Examples

optimizer_gwo()

metANN documentation built on May 16, 2026, 1:06 a.m.