Results 251 to 260 of about 3,109,206 (294)

Chaotic particle swarm optimization

Proceedings of the first ACM/SIGEVO Summit on Genetic and Evolutionary Computation, 2009
A new particle swarm optimization (PSO) algorithm with has a chaotic neural network structure, is proposed. The structure is similar to the Hopfield neural network with transient chaos, and has an improved ability to search for globally optimal solution and does not suffer from problems of premature convergence. The presented PSO model is discrete-time
Yanxia Sun 0001, Guoyuan Qi, Zenghui Wang 0001, Barend J. van Wyk, Yskandar Hamam   +4 more
openaire   +2 more sources

Simplifying Particle Swarm Optimization

Applied Soft Computing, 2010
The general purpose optimization method known as Particle Swarm Optimization (PSO) has received much attention in past years, with many attempts to find the variant that performs best on a wide variety of optimization problems. The focus of past research has been with making the PSO method more complex, as this is frequently believed to increase its ...
M. E. H. Pedersen, Andrew J. Chipperfield   +1 more
openaire   +2 more sources

Monitoring of particle swarm optimization

Frontiers of Computer Science in China, 2009
In this paper, several diversity measurements will be discussed and defined. As in other evolutionary algorithms, first the population position diversity will be discussed followed by the discussion and definition of population velocity diversity which is different from that in other evolutionary algorithms since only PSO has the velocity parameter ...
Yuhui Shi 0001, Russell C. Eberhart
openaire   +1 more source

Vortex Particle Swarm Optimization

2013 IEEE Congress on Evolutionary Computation, 2013
This paper presents an optimization algorithm based on self-propelled particle swarms which exploit vorticity features in order to avoid local minima; the proposed algorithm is termed Vortex Particle Swarm Optimization (VPSO). The optimization algorithm switches between translational and dispersion behavior of the swarm to enhance the exploration of ...
Helbert E. Espitia, Jorge I. Sofrony
openaire   +1 more source

Tournament Particle Swarm Optimization

2007 IEEE Symposium on Computational Intelligence and Games, 2007
This paper introduces tournament particle swarm optimization (PSO) as a method to optimize weights of game tree evaluation functions in a competitive environment using particle swarm optimization. This method makes use of tournaments to ensure a fair evaluation of the performance of particles in the swarm, relative to that of other particles.
Willem H. Duminy, Andries P. Engelbrecht
openaire   +2 more sources

Cellular Particle Swarm Optimization

Information Sciences, 2011
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Guo Hui Zhang, Liang Gao
exaly   +4 more sources

Particle swarm optimization in a nutshell

Proceedings of the International Conference and Workshop on Emerging Trends in Technology, 2010
Swarm intelligence is the collective intelligence of group of independent agents. It can be applied in optimization. So researchers are increasingly interested in swarm Intelligence. The paper describes the swarm Intelligence. Paper discusses type of biological system - social system, more specifically while focusing on the aspects of developments of ...
Snehal Kamalapur, Shirish Sane
openaire   +1 more source

Oscillatory Particle Swarm Optimizer

Applied Soft Computing, 2018
Abstract The Particle Swarm Optimization (PSO) algorithm is an attractive meta-heuristic approach for difficult optimization problems. It is able to produce satisfactory results when classical analytic methods cannot be applied. However, the design of PSO was usually based on ad-hoc attempts and its behavior could not be exactly specified.
Haiyan Shi, Shilong Liu 0006, Hongkun Wu, Ruowei Li, San Chi Liu, Ngai Ming Kwok, Yeping Peng   +6 more
openaire   +2 more sources

Interactive particle swarm optimization

5th International Conference on Intelligent Systems Design and Applications (ISDA'05), 2005
It is often desirable to simultaneously handle several objectives and constraints in practical optimization problems. In some cases, these objectives and constraints are non-commensurable and they are not explicitly/mathematically available. For this kind of problems, interactive optimization may be a good approach.
János Madár, János Abonyi, Ferenc Szeifert   +2 more
openaire   +2 more sources

Catfish particle swarm optimization

2008 IEEE Swarm Intelligence Symposium, 2008
Catfish particle swarm optimization (CatfishPSO) is a novel optimization algorithm proposed in this paper. The mechanism is dependent on the incorporation of a catfish particle into the linearly decreasing weight particle swarm optimization (LDWPSO). The introduced catfish particle improves the performance of LDWPSO.
Li-Yeh Chuang, Sheng-Wei Tsai, Cheng-Hong Yang 0001   +2 more
openaire   +1 more source