This paper proposes improvements to the binary grey-wolf optimizer (BGWO) solve feature selection (FS) problem associated with high data dimensionality, irrelevant, noisy, and redundant that will then allow machine learning algorithms attain better classification/clustering accuracy in less training time.We propose three variants of BGWO addition standard variant, applying different transfer fu...

Artificial Neural Networks (ANNs) are utilized to solve a variety of problems in many domains. In this type network, training and selecting parameters that define networks architecture play an important role enhancing the accuracy network's output; Therefore, Prior training, those must be optimized. Grey Wolf Optimizer (GWO) has been considered one efficient developed approaches Swarm Intellige...

 In this research, a tri-objective mathematical model is proposed for the Transportation-Location-Routing problem. The model considers a three-echelon supply chain and aims to minimize total costs, maximize the minimum reliability of the traveled routes and establish a well-balanced set of routes. In order to solve the proposed model, four metaheuristic algorithms, including Multi-Objective Gre...

Grey wolf optimizer (GWO) is a new technique, which can be applied successfully for solving optimized problems. The GWO indeed simulates the leadership hierarchy and hunting mechanism of grey wolves. There are four types of grey wolves which are alpha, beta, delta and omega. Those four types can be used for simulating the leadership hierarchy. In order to complete the process of GWO a three mai...

Evolutionary Population Dynamics (EPD) refers to eliminating poor individuals in nature, which is the opposite of survival fittest. Although this method can improve median whole population meta-heuristic algorithms, it suffers from exploration capability handle high-dimensional problems. This paper proposes a novel EPD operator search process. In other words, as primary mainly improves fitness ...

Feature selection in Arabic text is a challenging task due to the complex and rich nature of Arabic. The feature requires solution quality, stability, conver- gence speed, ability find global optimal. This study proposes method using Hybrid Binary Gray Wolf Optimizer (HBGWO) for Ara- bic classification. HBGWO combines local search capabilities or exploratory BGWO around best solutions exploits ...

The insurance industry is based on risk calculations, high profits, and detailed information. predictive models that companies utilize allow to make accurate decisions about the sector. This research focuses improving accuracy of predicting customers Property Casualty (P&C) insurance. In this study, a reliable quantitative analytical big data method has been developed, Hybrid Grey Wolf Whal...