Particle swarm optimization (PSO) has been in practice for more than 10 years now and has gained wide popularity in various optimization tasks. In the context to single objective ...
Particle Swarm Optimization (PSO) is a population-based optimization method in which search points employ a cooperative strategy to move toward one another. In this paper we show ...
Andrew M. Sutton, Darrell Whitley, Monte Lunacek, ...
We apply an adapted version of Particle Swarm Optimization to distributed unsupervised robotic learning in groups of robots with only local information. The performance of the lea...
Abstract. In this paper we present an estimation of distribution particle swarm optimization algorithm that borrows ideas from recent developments in ant colony optimization. In th...
The following article describes and discusses the suitability of the particle swarm optimization (PSO) for the employment with blind adaptation of the directional characteristic o...
Abstract. In this paper, five previous Particle Swarm Optimization (PSO) algorithms for multimodal function optimization are reviewed. A new and a successful PSO based algorithm, n...
The current paper uses a scenario from logistics to show that modern heuristics, and in particular particle swarm optimization (PSO) can significantly add to the improvement of sta...
Landing on distant planets is always a challenging task due to the distance and hostile environments found. In the design of autonomous hazard avoidance systems we find the particu...
In optimization problems involving large amounts of data, such as web content, commercial transaction information, or bioinformatics data, individual function evaluations may take ...
Andrew W. McNabb, Christopher K. Monson, Kevin D. ...
In this work we compare the use of a Particle Swarm Optimization (PSO) and a Genetic Algorithm (GA) (both augmented with Support Vector Machines SVM) for the classification of high...