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 article, an Improved Grey Wolf Optimizer (I-GWO) is proposed for solving global optimization and engineering design problems. This improvement is proposed to alleviate …
Y Hou, H Gao, Z Wang, C Du - Sensors, 2022 - mdpi.com
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 …
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 …
Meta-heuristic search algorithms were successfully used to solve a variety of problems in engineering, science, business, and finance. Meta-heuristic algorithms share common …
Searching for the optimal subset of features is known as a challenging problem in feature selection process. To deal with the difficulties involved in this problem, a robust and reliable …
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 …
M Braik, MH Ryalat, H Al-Zoubi - Neural Computing and Applications, 2022 - Springer
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 …
AA Heidari, P Pahlavani - Applied Soft Computing, 2017 - Elsevier
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 …