Particle swarm optimization (PSO) is a stochastic algorithm, used for the optimization
problems, proposed by Kennedy [1] in 1995. PSO is a recognized algorithm for optimization …

Particle swarm optimization (PSO) is a stochastic, population-based optimization method,
which has been applied successfully to a wide range of problems. However, PSO is …

Particle Swarm Optimization (PSO) algorithm has shown good performance in many
optimization problems, but PSO suffers from the problem of early convergence into a local …

Particle Swarm Optimization, a population based optimization technique has been used in
wide number of application areas to solve optimization problems. This paper presents a new …

An opposition-mutation-based particle swarm optimization algorithm is presented (OMPSO)
in this paper. The proposed OMPSO employs opposition-based learning algorithms, which …

Particle swarm optimization (PSO) is a new stochastic optimization technique based on
swarm intelligence. In this paper, we introduce the basic principles of PSO firstly. Then, the …

The widespread and increasing application of Particle Swarm Optimizer (PSO) algorithms in
both theoretical and practical fields leads to further considerations and new developments …

Particle swarm optimization (PSO) is a stochastic population-based algorithm that is
designed for real-parameter optimization problems. PSO is a simple and powerful algorithm …

A modified particle swarm optimization (PSO) algorithm is proposed in this paper to avoid
premature convergence with the introduction of mutation operation. The performance of this …

This paper proposed an novel improved particle swarm optimizer algorithm based on
random perturbations (PSO-RP) with global convergence performance. Random …