One issue in applying PSO is to find a good working set of parameters. The standard settings are often work sufficiently but don't exhaust the possibilities of PSO. This paper proposes an extended Meta-PSO approach to optimize the PSO parameters as well as the neighborhood topology for a given problem by PSO itself. It is applied to four typical benchmark functions known from literature. The good results indicate that PSO is capable of optimizing itself
Particle Swarm Optimization (PSO) is an algorithm for swarm intelligence based on stochastic and pop...
: Particel Swarm Optimization (PSO) is a form of population evolutionary algorithm introduced in the...
This paper presents the extension of the meta particle swarm optimization (Meta-PSO) evolutionary al...
Particle Swarm Optimization is a simple and elegant optimization algorithm used to solve a large var...
Meta-PSO has been recently developed as an enhancement of the particle swarm optimization (PSO) meth...
What attributes and settings of the Particle Swarm Optimizer constants result in a good, off-the-she...
This work deals with particle swarm optimization. The theoretic part briefly describes the problem o...
The particle swarm algorithm is a computational method to optimize a problem iteratively. As the nei...
The general purpose optimization method known as Particle Swarm Optimization (PSO) has received much...
Meta-heuristic PSO has limits, such as premature convergence and high running time, especially for c...
Recently, the Particle Swarm Optimization (PSO) method has been successfully applied to many differe...
International audiencePSO-2S is a multi-swarm PSO algorithm using charged particles in a partitioned...
This paper presents a combination method of Particle Swarm Optimization (PSO) and topology optimizat...
Particle swarm optimization (PSO) is one of the most well-regarded swarm-based algorithms in the lit...
Reconnue depuis de nombreuses années comme une méthode efficace pour la résolution de problèmes diff...
Particle Swarm Optimization (PSO) is an algorithm for swarm intelligence based on stochastic and pop...
: Particel Swarm Optimization (PSO) is a form of population evolutionary algorithm introduced in the...
This paper presents the extension of the meta particle swarm optimization (Meta-PSO) evolutionary al...
Particle Swarm Optimization is a simple and elegant optimization algorithm used to solve a large var...
Meta-PSO has been recently developed as an enhancement of the particle swarm optimization (PSO) meth...
What attributes and settings of the Particle Swarm Optimizer constants result in a good, off-the-she...
This work deals with particle swarm optimization. The theoretic part briefly describes the problem o...
The particle swarm algorithm is a computational method to optimize a problem iteratively. As the nei...
The general purpose optimization method known as Particle Swarm Optimization (PSO) has received much...
Meta-heuristic PSO has limits, such as premature convergence and high running time, especially for c...
Recently, the Particle Swarm Optimization (PSO) method has been successfully applied to many differe...
International audiencePSO-2S is a multi-swarm PSO algorithm using charged particles in a partitioned...
This paper presents a combination method of Particle Swarm Optimization (PSO) and topology optimizat...
Particle swarm optimization (PSO) is one of the most well-regarded swarm-based algorithms in the lit...
Reconnue depuis de nombreuses années comme une méthode efficace pour la résolution de problèmes diff...
Particle Swarm Optimization (PSO) is an algorithm for swarm intelligence based on stochastic and pop...
: Particel Swarm Optimization (PSO) is a form of population evolutionary algorithm introduced in the...
This paper presents the extension of the meta particle swarm optimization (Meta-PSO) evolutionary al...