Novel Grey Wolf Optimization Algorithm (EGWO)

Enhanced Grey Wolf Optimization with cubic parameter control and dynamic wolf position updating for improved exploration and exploitation.

The proposed Enhanced Grey Wolf Optimization (EGWO) algorithm is a novel improvement of the original Grey Wolf Optimizer (GWO) designed to enhance exploration and exploitation capabilities.

The algorithm improves the search performance by introducing a cubic update mechanism for the control parameter (a), which provides a better transition between exploration and exploitation phases. Additionally, a dynamic weighted position updating strategy is incorporated to improve convergence behavior and maintain an effective balance between global and local search.

This MATLAB implementation provides a flexible framework for solving continuous optimization problems using user-defined objective functions. EGWO can be applied to benchmark optimization problems and various engineering applications.

Key features:

• Enhanced exploration and exploitation capability

• Cubic parameter update mechanism

• Adaptive alpha-beta-delta based position updating

• Improved convergence characteristics

• Easy integration with custom objective functions

Reference:

Original Grey Wolf Optimizer:

S. Mirjalili, S. M. Mirjalili, A. Lewis,

"Grey Wolf Optimizer,"

Advances in Engineering Software, 2014.

DOI: 10.1016/j.advengsoft.2013.12.007

Proposed EGWO:

P. Samal et al.,

"A Novel Grey Wolf Optimization Algorithm with Enhanced Exploration, and Exploitation Ability,"

2025 International Conference on Power Electronics and Energy (ICPEE).

DOI: 10.1109/ICPEE65973.2025.11411565