Grey wolf optimizer (GWO) is one of recent metaheuristics swarm intelligence methods. It
has been widely tailored for a wide variety of optimization problems due to its impressive …

ABSTRACT The Internet of Things (IoT) is a relatively new technology that has piqued
academics' and business information systems' attention in recent years. The Internet of …

In this article, an Improved Grey Wolf Optimizer (I-GWO) is proposed for solving global
optimization and engineering design problems. This improvement is proposed to alleviate …

This paper introduces the Human Evolutionary Optimization Algorithm (HEOA), a
metaheuristic algorithm inspired by human evolution. HEOA divides the global search …

In nature, the eastern North American monarch population is known for its southward
migration during the late summer/autumn from the northern USA and southern Canada to …

For data mining tasks on high-dimensional data, feature selection is a necessary pre-
processing stage that plays an important role in removing redundant or irrelevant features …

In this paper, a new kind of swarm-based metaheuristic search method, called Elephant
Herding Optimization (EHO), is proposed for solving optimization tasks. The EHO method is …

This paper proposed an improved Grey Wolf Optimizer (GWO) to resolve the problem of
instability and convergence accuracy when GWO is used as a meta-heuristic algorithm with …

This paper presents a novel meta-heuristic algorithm called Ali Baba and the forty thieves
(AFT) for solving global optimization problems. Recall the famous tale of Ali Baba and the …

The grey wolf optimizer (GWO) is a new efficient population-based optimizer. The GWO
algorithm can reveal an efficient performance compared to other well-established …