DocumentCode :
2703626
Title :
A Novel Method for Solving Fuzzy Programming Based on Hybrid Particle Swarm Optimization
Author :
Pei, Zhenkui ; Tian, ShengFeng ; Huang, Houkuan
Author_Institution :
Beijing Jiaotong Univ., Beijing
fYear :
2007
fDate :
15-19 Dec. 2007
Firstpage :
216
Lastpage :
219
Abstract :
Fuzzy programming offers a powerful means of handling optimization problems with fuzzy parameters. Fuzzy programming has been used in different ways in the past. The particle swarm optimization (PSO) has been applied successfully to continuous nonlinear constrained optimization problems, neural network, etc. But we have not been found to use PSO for fuzzy programming in literature. In this paper, we combined with fuzzy simulation, neural network and PSO to produce a hybrid intelligent algorithm. Based on this hybrid intelligent algorithm, we introduced for solving fuzzy expected value models. Some numerical examples are given to illustrate the algorithm is effective and powerful.
Keywords :
fuzzy set theory; neural nets; particle swarm optimisation; continuous nonlinear constrained optimization problems; fuzzy expected value models; fuzzy programming; fuzzy simulation; hybrid intelligent algorithm; hybrid particle swarm optimization; neural network; Birds; Competitive intelligence; Computational intelligence; Constraint optimization; Dynamic programming; Educational institutions; Fuzzy neural networks; Intelligent networks; Neural networks; Particle swarm optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Security Workshops, 2007. CISW 2007. International Conference on
Conference_Location :
Harbin
Print_ISBN :
978-0-7695-3073-4
Type :
conf
DOI :
10.1109/CISW.2007.4425483
Filename :
4425483
Link To Document :
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