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 …

In this paper, a review on the three most important communication techniques (ground,
aerial, and underwater vehicles) has been presented that throws light on trajectory planning …

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 …

Metaheuristics are an impressive area of research with extremely important improvements in
the solution of intractable optimization problems. Major advances have been made since the …

Autonomous navigation is significant to UAVs, especially in disaster scenarios. A Hybrid
GWO and Differential Evolution (HGWODE) algorithm is developed to solve UAV path …

Quickly, accurately and reliably extract the parameters of solar photovoltaic (PV) model is
very critical to simulate, evaluate and control the PV systems. During the past few years …

The purpose of this study is to offer a high-performance machine learning model for
determining the ultimate load-carrying capability of concrete-filled steel tube (CFST) …

In this article, an improved variant of the grey wolf optimizer (GWO) named gaze cues
learning-based grey wolf optimizer (GGWO) is proposed. The main intentions are to reduce …

Abstract The Tunicate Swarm Algorithm (TSA) inspires by simulating the lives of Tunicates at
sea and how food is obtained. This algorithm is easily entrapped to local optimization …

Grey wolf optimizer is a novel swarm intelligent algorithm. It has received lots of interest from
the heuristic algorithm community for its superior optimization capacity and few parameters …