DocumentCode :
3423038
Title :
Hybrid particle swarm optimization algorithm for solving systems of nonlinear equations
Author :
Ouyang, Aijia ; Zhou, Yongquan ; Luo, Qifang
Author_Institution :
Coll. of Math. & Comput. Sci., Guangxi Univ. for Nat., Nanning, China
fYear :
2009
fDate :
17-19 Aug. 2009
Firstpage :
460
Lastpage :
465
Abstract :
A hybrid particle swarm optimization (HPSO) algorithm, which combines the advantages of Nelder-Mead simplex method (SM) and particle swarm optimization (PSO) algorithm, is put forward to solve systems of nonlinear equations, and it can be used to overcome the difficulty in selecting good initial guess for SM and inaccuracy of PSO due to being easily trapped into local optimal. The algorithm has sufficiently displayed the performance of PSO´s global searching and SM´s accurate local search. Numerical computation results show that the approach has great robust, high convergence rate and precision, it can give satisfactory solutions of nonlinear equations.
Keywords :
constraint theory; nonlinear equations; particle swarm optimisation; problem solving; Nelder-Mead simplex method; PSO; hybrid particle swarm optimization algorithm; local search; nonlinear equations; Birds; Computer science; Convergence of numerical methods; Educational institutions; Information security; Mathematics; Nonlinear equations; Particle swarm optimization; Robustness; Samarium; particle swarm optimization algorithm; simplex method; systems of nonlinear equations;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Granular Computing, 2009, GRC '09. IEEE International Conference on
Conference_Location :
Nanchang
Print_ISBN :
978-1-4244-4830-2
Type :
conf
DOI :
10.1109/GRC.2009.5255079
Filename :
5255079
Link To Document :
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