A genetic algorithm (GA) is an evolutionary algorithm inspired by the natural selection and
biological processes of reproduction of the fittest individual. GA is one of the most popular …

Applications of machine learning (ML) methods have been used extensively to solve various
complex challenges in recent years in various application areas, such as medical, financial …

This study presents a novel physics-based metaheuristic algorithm called Kepler
optimization algorithm (KOA), inspired by Kepler's laws of planetary motion to predict the …

This study tenders a new nature-inspired metaheuristic algorithm (MA) based on the
behavior of the Genghis Khan shark (GKS), called GKS optimizer (GKSO), which is used for …

Optimization techniques, particularly meta-heuristic algorithms, are highly effective in
optimizing and enhancing efficiency across diverse models and systems, renowned for their …

An original swarm-based, bio-inspired metaheuristic algorithm, named electric eel foraging
optimization (EEFO) is developed and tested in this work. EEFO draws inspiration from the …

Currently, meta-heuristic algorithms have been widely studied and applied, but balancing
exploration and exploitation remains a challenge. In this study, a novel meta-heuristic …

This study proposes a new nature-inspired metaheuristic that mimics the behaviour of the
prairie dogs in their natural habitat called the prairie dog optimization (PDO). The proposed …

This paper proposes a novel swarm intelligence bioinspired optimization algorithm, called
the Dandelion Optimizer (DO), for solving continuous optimization problems. DO simulates …

Metaheuristic algorithms are intelligent optimization approaches that lead the searching
procedure through utilizing exploitation and exploration. The increasing complexity of real …