We investigate the runtime of the Binary Particle Swarm Optimization (PSO) algorithm introduced by Kennedy and Eberhart (1997). The Binary PSO maintains a global best solution and...
Particle filtering is an effective sequential Monte Carlo approach to solve the recursive Bayesian filtering problem in non-linear and non-Gaussian systems. The algorithm is base...
This paper presents an overview of our most recent results concerning the Particle Swarm Optimization (PSO) method. Techniques for the alleviation of local minima, and for detectin...
Abstract— The Particle Swarm Optimization (PSO) algorithm is a robust stochastic evolutionary computation technique based on the movement and intelligence of swarms. This paper p...
The interaction among particles is a vital aspect of Particle Swarm Optimization. As such, it has a strong influence on the swarm’s success. In this study various approaches re...