The optimization problems are becoming more complicated, requiring new and efficient
optimization techniques to solve them. Many bio-inspired meta-heuristic algorithms have …

Abstract The Firefly Algorithm (FA) is a highly efficient population-based optimization
technique developed by mimicking the flashing behavior of fireflies when mating. This article …

This paper discusses the merging of two optimization algorithms, atom search optimization
and particle swarm optimization, to create a hybrid algorithm called hybrid atom search …

Feature selection is a multi-objective optimization problem since it has two conflicting
objectives: maximizing the classification accuracy and minimizing the number of the …

Abstract Kepler Optimization Algorithm (KOA) is a physically based meta-heuristic algorithm
inspired by Kepler's laws to simulate planetary motions, KOA shows strong performance on …

Particle swarm optimization (PSO) is one of the most classical metaheuristic algorithms that
has gained significant attention since its inception. It has some inherent advantages, such as …

Since the exploration of multiple solution sets will lead to the deterioration of convergence in
multi-objective particle swarm optimization, the motion of the particles is severely disturbed …

Particle swarm optimization (PSO) has been used extensively in numerical and engineering
optimization problems in the last decades. However, due to drawbacks such as a single …

Particle swarm optimization algorithms are often applied to solve optimization problems.
However, the traditional particle swarm optimization algorithm has a single search method …

As an influential technology of swarm evolutionary computing (SEC), the particle swarm
optimization (PSO) algorithm has attracted extensive attention from all walks of life …