Autonomous groups of particles swarm optimization (AGPSO), inspired by individual
diversity in biological swarms such as insects or birds, is a modified particle swarm …

In this paper, a modified particle swarm optimization (PSO) algorithm called autonomous
groups particles swarm optimization (AGPSO) is proposed to further alleviate the two …

In order to mitigate the problems of premature convergence and low search accuracy that
exist in traditional particle swarm optimization (PSO), this paper presents PSO with …

Over the last two decades, the newly developed optimization technique–Particle Swarm
Optimization (PSO) has attracted great attention. Two common criticisms exist. First, most …

This paper presents a new variant of particle swarm optimization (PSO) algorithm named
guided adaptive search-based particle swarm optimizer (GuASPSO). In this algorithm, the …

Premature convergence has been recognized as one of the major drawbacks of particle
swarm optimization (PSO) algorithms. In particular, the lack of diversity in PSO performance …

Particle swarm optimization (PSO) is a heuristic optimization technique which was inspired
by flocking and swarming behavior of birds and insects. Same as other swarm intelligent …

Although particle swarm optimization algorithm (PSO) has displayed promising performance
on many optimization problems, how to balance contradictions between the exploration and …

Particle swarm optimization (PSO) is one of the well-known population-based techniques
used in global optimization and many engineering problems. Despite its simplicity and …

The particle swarm optimization algorithm (PSO) is a meta‐heuristic algorithm with swarm
intelligence. It has the advantages of easy implementation, high convergence accuracy, and …