Process / pipeline

Grey Wolf Optimizer — GWO

The Grey Wolf Optimizer (GWO) is a swarm-intelligence metaheuristic introduced by Mirjalili, Mirjalili, and Lewis in 2014 that models the social hierarchy and cooperative hunting behaviour of grey wolves. A population of candidate solutions is divided into four leadership ranks — alpha, beta, delta, and omega — and the three best solutions at each iteration guide the entire swarm toward increasingly better regions of the search space.

Open in MethodMindSoonVideoSoon

Read the full method

Members only

Sign in with a free account to read this section.

Sign in

Sources

  1. Mirjalili, S., Mirjalili, S. M., & Lewis, A. (2014). Grey Wolf Optimizer. Advances in Engineering Software, 69, 46-61. DOI: 10.1016/j.advengsoft.2013.12.007
  2. Faris, H., Aljarah, I., Al-Betar, M. A., & Mirjalili, S. (2018). Grey Wolf Optimizer: A Review of Recent Variants and Applications. Neural Computing and Applications, 30(2), 413-435. DOI: 10.1007/s00521-018-3662-6

Related methods

Referenced by

ScholarGateGrey Wolf Optimizer (Grey Wolf Optimizer (GWO)). Retrieved 2026-06-04 from https://scholargate.app/en/optimization/grey-wolf-optimizer