Abstract

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.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.