Abstract The Mountain Gazelle Optimizer (MGO), a novel meta-heuristic algorithm inspired
by the social life and hierarchy of wild mountain gazelles, is suggested in this paper. In this …

Feature selection has become an indispensable machine learning process for data
preprocessing due to the ever-increasing sizes in actual data. There have been many …

A new nature-inspired optimization method, named the Golden Jackal Optimization (GJO)
algorithm is proposed, which aims to provide an alternative optimization method for solving …

Metaheuristics play a critical role in solving optimization problems, and most of them have
been inspired by the collective intelligence of natural organisms in nature. This paper …

Metaheuristics play a crucial role in solving optimization problems. The majority of such
algorithms are inspired by collective intelligence and foraging of creatures in nature. In this …

As the world moves towards industrialization, optimization problems become more
challenging to solve in a reasonable time. More than 500 new metaheuristic algorithms …

This paper proposes a new metaheuristic optimization algorithm based on ancient war
strategy. The proposed War Strategy Optimization (WSO) is based on the strategic …

A new bio-inspired optimization technique, named Manta Ray Foraging Optimization
(MRFO) algorithm, is proposed and presented, aiming to providing a novel algorithm that …

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 …

Selecting relevant feature subsets is vital in machine learning, and multiclass feature
selection is harder to perform since most classifications are binary. The feature selection …