Using quantum-behaved particle swarm optimization algorithm to solve non-linear programming problems

DOI10.1080/00207160601170254zbMath1116.65072OpenAlexW1998909776MaRDI QIDQ3445874

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Publication date: 7 June 2007

Published in: International Journal of Computer Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207160601170254

zbMATH Keywords

heuristicsnumerical examplesevolutionary computationparticle swarm optimizationnon-linear programmingquantum behaviour

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Nonlinear programming (90C30) Stochastic programming (90C15) Dynamic programming (90C39)

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A novel PSO model based on simulating human social communication behavior ⋮ QPSO-CD: quantum-behaved particle swarm optimization algorithm with Cauchy distribution ⋮ An improved quantum-behaved particle swarm optimization and its application to medical image registration ⋮ An improved quantum-behaved particle swarm optimization for multi-peak optimization problems ⋮ Multiple sequence alignment using the hidden Markov model trained by an improved quantum-behaved particle swarm optimization ⋮ Pareto optimal mapping for tile-based network-on-chip under reliability constraints ⋮ Training algorithm for radial basis function neural network based on quantum-behaved particle swarm optimization

Cites Work

• Searching nonlinear functions for high values
• A study of particle swarm optimization particle trajectories

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