Research on Fuzzy Adaptive Optimization Strategy of Particle Swarm Algorithm
نویسندگان
چکیده
This paper introduces a novel fuzzy adaptive optimization strategy (FAOPSO) for the particle swarm algorithm. Initially, to avoid falling into local optimums, the information of multioptimum distribution state is introduced into the particle swarm movement programming. However, in this kind of multi-optimum static programming mode (MSPPSO), the programming proportion factor of multi-optimum cannot be dynamically adjusted in the optimization process. On the basis of MSPPSO, a kind of fuzzy adaptive programming strategy based on double-variable and single-dimensional fuzzy control structure is proposed and the performance of FAOPSO is also observed. The proposed approach is validated by function optimization problem from the standard literature. Simulation results indicated that the approach is highly competitive for its better general convergence performance.
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