Bat algorithm (BA) is one of the promising metaheuristic algorithms. It proved its efficiency in
dealing with various optimization problems in diverse fields, such as power and energy …

This paper introduces a comprehensive survey of a new population-based algorithm so-
called gradient-based optimizer (GBO) and analyzes its major features. GBO considers as …

This paper proposes a novel population-based optimization method, called Aquila Optimizer
(AO), which is inspired by the Aquila's behaviors in nature during the process of catching the …

Cloud-fog computing frameworks are emerging paradigms developed to add benefits to the
current Internet of Things (IoT) architectures. In such frameworks, task scheduling plays a …

The central cloud facilities based on virtual machines offer many benefits to reduce the
scheduling costs and improve service availability and accessibility. The approach of cloud …

This paper introduces a comprehensive survey of a new swarm intelligence optimization
algorithm so-called Harris hawks optimization (HHO) and analyzes its major features. HHO …

Text clustering is one of the efficient unsupervised learning techniques used to partition a
huge number of text documents into a subset of clusters. In which, each cluster contains …

Instead of the cloud, the Internet of things (IoT) activities are offloaded into fog computing to
boost the quality of services (QoSs) needed by many applications. However, the availability …

The lightning search algorithm (LSA) is a novel meta-heuristic optimization method, which is
proposed in 2015 to solve constraint optimization problems. This paper presents a …

This paper thoroughly introduces a comprehensive review of the so-called Dragonfly
algorithm (DA) and highlights its main characteristics. DA is considered one of the promising …