Particle swarm optimization (PSO) is one of the most well-regarded swarm-based algorithms
in the literature. Although the original PSO has shown good optimization performance, it still …

Particle swarm optimization (PSO) has undergone many changes since its introduction in
1995. As researchers have learned about the technique, they have derived new versions …

Swarm intelligence refers to a kind of problem-solving ability that emerges in the interactions
of simple information-processing units. The concept of a swarm suggests multiplicity …

Evolutionary computation techniques, genetic algorithms, evolutionary strategies and
genetic programming are motivated by the evolution of nature. A population of individuals …

The particle swarm algorithm adjusts the trajectories of a population of" particles" through a
problem space on the basis of information about each particle's previous best performance …

Metaheuristics are widely recognized as efficient approaches for many hard optimization
problems. This paper provides a survey of some of the main metaheuristics. It outlines the …

This paper focuses on the engineering and computer science aspects of developments,
applications, and resources related to particle swarm optimization. Developments in the …

We empirically study the performance of the particle swarm optimizer (PSO). Four different
benchmark functions with asymmetric initial range settings are selected as testing functions …

Parameter selection in particle swarm optimization Page 1 Parameter Selection in Particle
Swarm Optimization Yuhui Shi and Russell C. Eberhart Department of Electrical Engineering …

Computational Intelligence: An Introduction, Second Edition offers an in-depth exploration
into the adaptive mechanisms that enable intelligent behaviour in complex and changing …