What is it about?
This paper aims at studying meta-heuristic algorithms. One of the common meta-heuristic optimization algorithms is called grey wolf optimization (GWO). The key aim is to enhance the limitations of the wolves’ searching process of attacking gray wolves.
Photo by Eva Blue on Unsplash
Why is it important?
The development of meta-heuristic algorithms has increased by researchers to use them extensively in the field of business, science and engineering. In this paper, the K-means clustering algorithm is used to enhance the performance of the original GWO; the new algorithm is called K-means clustering gray wolf optimization (KMGWO).
Read the Original
This page is a summary of: A new K-means grey wolf algorithm for engineering problems, World Journal of Engineering, March 2021, Emerald, DOI: 10.1108/wje-10-2020-0527.
You can read the full text:
The following have contributed to this page