Results 251 to 260 of about 82,578 (301)

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
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Dispersed particle swarm optimization

Information Processing Letters, 2008
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Xingjuan Cai, Zhihua Cui, Jianchao Zeng 0001, Ying Tan 0003   +3 more
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Particle Swarm Optimizer for constrained optimization

2013 IEEE Congress on Evolutionary Computation, 2013
Recently, Particle Swarm Optimizer (PSO) has become a popular tool for solving constrained optimization problems. However, there is no guarantee that PSO will perform consistently well for all problems and will not be trapped in local optima. In this paper, a PSO algorithm is introduced that uses two new mechanisms, the first one to maintain a better ...
Samir M. Mohamed Elsayed, Ruhul A. Sarker, Efrén Mezura-Montes   +2 more
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Grey particle swarm optimization

Applied Soft Computing, 2012
With the help of grey relational analysis, this study attempts to propose two grey-based parameter automation strategies for particle swarm optimization (PSO). One is for the inertia weight and the other is for the acceleration coefficients. By the proposed approaches, each particle has its own inertia weight and acceleration coefficients whose values ...
Min-Shyang Leu, Ming-Feng Yeh
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Particle Swarm Optimization with Opposite Particles

2005
The particle swarm optimization algorithm is a kind of intelligent optimization algorithm. This algorithm is prone to be fettered by the local optimization solution when the particle's velocity is small. This paper presents a novel particle swarm optimization algorithm named particle swarm optimization with opposite particles which is guaranteed to ...
Rujing Wang, Xiaoming Zhang
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A hierarchical particle swarm optimizer

The 2003 Congress on Evolutionary Computation, 2003. CEC '03., 2004
A hierarchical version of the particle swarm optimization method called H-PSO is introduced. In H-PSO the particles are arranged in a dynamic hierarchy that is used to define a neighborhood structure. Depending on the quality of their so far best found solution the particles move up or down the hierarchy so that good particles have a higher influence ...
Stefan Janson, Martin Middendorf
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Adaptive particle swarm optimization

SMC'03 Conference Proceedings. 2003 IEEE International Conference on Systems, Man and Cybernetics. Conference Theme - System Security and Assurance (Cat. No.03CH37483), 2004
The particle swarm optimization (PSO) method is one of the most powerful methods for solving unconstrained and constrained global optimization problems. Little is, however, known about how the PSO method works or finds a globally optimal solution of a global optimization problem when the method is applied to global optimization problems.
Keiichiro Yasuda, Azuma Ide, Nobuhiro Iwasaki   +2 more
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Particle Swarm Optimization Programming

2010 International Conference on Computational Aspects of Social Networks, 2010
PSO is a parallel stochastic optimization algorithm with advantages of less parameters and high efficiency. This paper describes the programming problem in the method of two linear tables with discrete and continuous quantity, then uses discrete PSO algorithm to discrete optimization and continuous PSO to optimize continuous quantity in the solving ...
Xiaojun Wu, Ming Zhao, Yaohong Qu
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Ecosystem particle swarm optimization

Soft Computing, 2016
Particle swarm optimization (PSO) is a well-known swarm intelligence algorithm inspired by the foraging behavior of bird flocking. PSO has been widely used in many optimization and engineering problems due to its simplicity and efficiency, even though there still exist some disadvantages.
Jiao Liu, Di Ma, Teng-bo Ma, Wei Zhang
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Resampling in Particle Swarm Optimization

2013 IEEE Congress on Evolutionary Computation, 2013
Particle Swarm Optimization (PSO) is a population-based algorithm designed to find good solutions to optimization problems. Its characteristics have encouraged its adoption to tackle a variety of problems in different fields. However, when such problems are subject to noise, the performance of PSO suffers an immediate deterioration which demands the ...
Juan Rada-Vilela, Mengjie Zhang 0001, Mark Johnston   +2 more
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