Abstract Particle Swarm Optimization (PSO) algorithm is a nature-inspired meta-heuristic
that has been utilized as a powerful optimization tool in a wide range of applications since its …

Particle swarm optimization (PSO) is a population based meta-heuristic search algorithm
that has been widely applied to a variety of problems since its advent. In PSO, the inertial …

Particle swarm optimization (PSO) is a swarm intelligent stochastic optimization algorithm
inspired by social behavior. Due to the fast convergent speed, it gets easily trapped into a …

In this paper, a Multi-Swarm Self-Adaptive and Cooperative Particle Swarm Optimization
(MSCPSO) based on four sub-swarms is presented. In the proposed algorithm, several …

This paper proposes an information sharing mechanism (ISM) to improve the performance of
particle swarm optimization (PSO). The ISM allows each particle to share its best search …

Accelerating the convergence speed and avoiding the local optimal solution are two main
goals of particle swarm optimization (PSO). The very basic PSO model and some variants of …

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

Abstract In the original Particle Swarm Optimization (PSO), the particle position vectors
denote the potential solutions of the optimization problem. Then, the position vectors are …

In the field of swarm intelligence inspired algorithms, particle swarm optimization (PSO) is a
renowned meta-heuristic due to its simplicity, performance, and implementation. However …

Particle swarm optimization (PSO) algorithm is one of the most effective and popular swarm
intelligence algorithms. In this paper, based on comparative judgment, an improved particle …