Despite the simplicity of the whale optimization algorithm (WOA) and its success in solving
some optimization problems, it faces many issues. Thus, WOA has attracted scholars' …

Feature selection (FS) represents an optimization problem that aims to simplify and improve
the quality of highly dimensional datasets through selecting prominent features and …

In this paper, we proposed an enhanced reptile search algorithm (RSA) for global
optimization and selected optimal thresholding values for multilevel image segmentation …

There have been many algorithms created and introduced in the literature inspired by
various events observable in nature, such as evolutionary phenomena, the actions of social …

In the recent era, Metaheuristic Algorithms (MHs) are developed to tackle many and different
optimization problems. The merit of the MHs is not only its simplicity to understand but also …

The COVID-19 is one of the most significant obstacles that humanity is now facing. The use
of computed tomography (CT) images is one method that can be utilized to recognize …

This paper proposes an enhanced version of Equilibrium Optimizer (EO) called (EEO) for
solving global optimization and the optimal power flow (OPF) problems. The proposed EEO …

Medical technological advancements have led to the creation of various large datasets with
numerous attributes. The presence of redundant and irrelevant features in datasets …

This study presents the K-means clustering-based grey wolf optimizer, a new algorithm
intended to improve the optimization capabilities of the conventional grey wolf optimizer in …

Monkey king evolution (MKE) is a population-based differential evolutionary algorithm in
which the single evolution strategy and the control parameter affect the convergence and the …