Title :
Fuzzy Parameter Particle Swarm Optimization
Author :
Yadmellat, P. ; Salehizadeh, S.M.A. ; Menhaj, M.B.
Author_Institution :
Dept. of Electr. Eng., Amirkabir Univ. of Tech, Tehran
Abstract :
This paper proposes a new fuzzy tuned parameter particle swarm optimization (FPPSO) which remarkably outperforms the standard PSO as well as the previous fuzzy based approaches. Two benchmark functions with asymmetric initial range settings are used to validate the proposed algorithm and compare its performance with that of the other algorithms known as fuzzy based PSO. Numerical results indicate that FPPSO is considerably competitive due to its ability to find the functions´ global optimum as well as its better convergence performance..
Keywords :
convergence; fuzzy logic; fuzzy reasoning; fuzzy set theory; particle swarm optimisation; asymmetric initial range setting; benchmark function; convergence; fuzzy inference; fuzzy logic; fuzzy tuned parameter particle swarm optimization; Convergence of numerical methods; Fuzzy control; Fuzzy logic; Fuzzy sets; Fuzzy systems; Intelligent networks; Intelligent systems; Particle swarm optimization; Standards development; Topology; Fuzzy Control; Optimization; PSO; Swarm Intelligence;
Conference_Titel :
Intelligent Networks and Intelligent Systems, 2008. ICINIS '08. First International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-0-7695-3391-9
Electronic_ISBN :
978-0-7695-3391-9
DOI :
10.1109/ICINIS.2008.111
