Open AccessEaGWO: Extended algorithm of Grey Wolf Optimizer
Author(s) -
Abhishek Kumar,
Lekhraj,
Avjeet Singh,
Amit Kumar
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1998/1/012028
Subject(s) - convergence (economics) , heuristic , mathematical optimization , meta heuristic , friedman test , computer science , local optimum , algorithm , mathematics , statistical hypothesis testing , statistics , economics , economic growth
The Grey Wolf Optimizer (GWO) and their very recent improved algorithms have some limitations such as stagnation in local optima, slow convergence rate, and so forth. In order to overcome these limitations, we have proposed an algorithm of GWO, named Extended algorithm of GWO (EaGWO), that modifies the hunting equation and encircling equation of the original GWO. The proposed algorithm has been examined on twenty-three very renowned test functions and compared the results with basic GWO and other very recent variants of GWO. This research work also considers the Friedman ANOVA test to verify the effectiveness of the proposed methodology. Consequently, the findings of this work justify quite competitive performance compared to other meta-heuristic algorithms.