conference paper
Fuzzy adaptive particle swarm optimization
Yuhui Shia b, Russell C. Eberhartc d
- aEDS Embedded Systems Team, Kokomo, IN, USA
- bEDS Embedded Syst. Team, Kokomo, IN, USA
- cDepartment of Electrical and Computer Engineering, Purdue School of Engineering and Technology, Indianapolis, IN, USA
- d[Department of Electrical and Computer Engineering, Purdue School of Engineering and Technology, Indianapolis, IN, USA]
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Abstract
A fuzzy system is implemented to dynamically adapt the inertia weight of the particle swarm optimization algorithm (PSO). Three benchmark functions with asymmetric initial range settings are selected as the test functions. The same fuzzy system has been applied to all three test functions with different dimensions. The experimental results illustrate that the fuzzy adaptive PSO is a promising optimization method, which is especially useful for optimization problems with a dynamic environment.