Title :
Fuzzy adaptive particle swarm optimization
Author :
Shi, Yuhui ; Eberhart, Russell C.
Author_Institution :
EDS Embedded Syst. Team, Kokomo, IN, USA
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
Keywords :
adaptive systems; evolutionary computation; fuzzy systems; optimisation; asymmetric initial range settings; benchmark functions; dynamic environment; dynamic inertia weight adaptation; fuzzy adaptive particle swarm optimization; fuzzy system; particle swarm optimization algorithm; test functions; Benchmark testing; Embedded system; Equations; Evolutionary computation; Functional programming; Fuzzy systems; Genetic programming; Optimization methods; Particle swarm optimization; System testing;
Conference_Titel :
Evolutionary Computation, 2001. Proceedings of the 2001 Congress on
Conference_Location :
Seoul
Print_ISBN :
0-7803-6657-3
DOI :
10.1109/CEC.2001.934377
