Particle Swarm Optimization Programming

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@InProceedings{Wu:2010:CASoN,

• author = "Xiaojun Wu and Ming Zhao and Yaohong Qu",
• title = "Particle Swarm Optimization Programming",
• booktitle = "2010 International Conference on Computational Aspects of Social Networks (CASoN)",
• year = "2010",
• month = sep,
• pages = "397--400",
• abstract = "PSO is a parallel stochastic optimisation 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 optimisation and continuous PSO to optimise continuous quantity in the solving process respectively, based on these proposes the Particle Swarm Optimisation Programming algorithm. Finally, GP and PSOP algorithms are compared by applying them to solving programming problem respectively with three typical test functions, the results show that the PSOP algorithm has better convergence precision and stability than the GP algorithm.",
• keywords = "genetic algorithms, genetic programming, continuous PSO, convergence precision, discrete PSO algorithm, discrete optimization, parallel stochastic optimization algorithm, particle swarm optimization programming, particle swarm optimisation, stochastic programming",
• DOI = "doi:10.1109/CASoN.2010.96",
• notes = "sphere, Griewank, Rastrigin. Sch. of Autom., Northwestern Polytech. Univ., Xi'an, China Also known as \cite{5636594}",

}

Genetic Programming entries for Xiaojun Wu Ming Zhao Yaohong Qu

Citations