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Dynamic-PSO: An improved particle swarm optimizer
2015 IEEE Congress on Evolutionary Computation (CEC), 2015In this paper, a variant of particle swarm optimization (PSO) is presented to handle the problem of stagnation encounters in PSO which may lead to get it trapped in local optima and premature convergence particularly in multimodal problems. The proposed scheme Dynamic-PSO (DPSO) does not disturb the fast convergence characteristics of PSO by keeping ...
Nitin Saxena +3 more
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Robotic applications with Particle Swarm Optimization (PSO)
2013 International Conference on Control, Decision and Information Technologies (CoDIT), 2013Swarm Intelligence (SI) is inspired from the study of colonies of swarms in Nature. This paper introduces a study originated on swarm intelligence, Particle Swarm Optimization (PSO). Three case studies on one link arm, a SCARA robot and a electrohydraulic robot - are presented on both simulation and experimental base to show effectiveness and ...
M. Taylan Das +2 more
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θ-PSO: a new strategy of particle swarm optimization
Journal of Zhejiang University-SCIENCE A, 2008zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Zhong, Wei-Min, Li, Shao-Jun, Qian, Feng
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Cutting Parameters Optimization by Using Particle Swarm Optimization (PSO)
Applied Mechanics and Materials, 2007Cutting parameters play an essential role in the economics of machining. In this paper, particle swarm optimization (PSO), a novel optimization algorithm for cutting parameters optimization (CPO), was discussed comprehensively. First, the fundamental principle of PSO was introduced; then, the algorithm for PSO application in cutting parameters ...
J.G. Li +4 more
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A Review of Particle Swarm Optimization ( PSO) Algorithm
2022Particle swarm optimization (PSO) is a population- based stochastic optimization technique that is inspired by the intelligent collective behaviour of certain animals, such as flocks of birds or schools of fish. It has undergone numerous improvements since its debut in 1995. As academics became more familiar with the technique, they produced additional
Shaikh, Mubeen, Yadav, Dhananjay
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Optimizing Assembly Sequence Time Using Particle Swarm Optimization (PSO)
Applied Mechanics and Materials, 2013Assembly sequence planning (ASP) plays an important role in the production planning and should be optimized to minimize production time and cost when large numbers of parts and sub-assemblies are involved in the assembly process. Although the ASP problem has been tackled via a variety of optimization techniques, these techniques are often inefficient ...
Mukred, J. A. A. +2 more
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Particle swarm optimization (PSO) for reflector antenna shaping
IEEE Antennas and Propagation Society Symposium, 2004., 2004It has been shown that reflector antenna systems can benefit substantially from careful shaping of the main or sub-reflectors, or both, in order to maximize the antenna's performance (Duan, D.-W. and Rahmat-Samii, Y., 1995). Shaped reflectors can be used to achieve high efficiencies and gains, low side-lobe levels, and arbitrarily contoured beams.
D. Gies, Y. Rahmat-Samii
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PSO+: A nonlinear constraints-handling particle swarm optimization
2016 IEEE Congress on Evolutionary Computation (CEC), 2016This paper proposes a new approach to Particle Swarm Optimization (PSO) to solve nonlinear problems with linear and nonlinear constraints. A crossover operator and a new particle updating method, named Footholds Concept, were developed to guarantee fully feasible solutions and better search-space coverage, respectively.
Manoela Kohler +4 more
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Fuzzy PSO: a generalization of particle swarm optimization
Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005., 2006In standard particle swarm optimization (PSO), the best particle in each neighborhood exerts its influence over other particles in the neighborhood. In this paper, we propose fuzzy PSO, a generalization which differs from standard PSO in the following respect: charisma is defined to be a fuzzy variable, and more than one particle in each neighborhood ...
A.M. Abdelbar +2 more
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Self-modeling curve resolution (SMCR) by particle swarm optimization (PSO)
Analytica Chimica Acta, 2007Particle swarm optimization (PSO) combined with alternating least squares (ALS) is introduced to self-modeling curve resolution (SMCR) in this study for effective initial estimate. The proposed method aims to search concentration profiles or pure spectra which give the best resolution result by PSO. SMCR sometimes yields insufficient resolution results
Hideyuki, Shinzawa +4 more
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