A Fast PSO Algorithm Based on Alpha-stable Mutation and Its Application in Aerodynamic Optimization

EasyChair Preprint 45

Abstract

In order to balance the global and local search ability of the basic particle swarm optimization (PSO) in the evolution loop, an alpha-stable distribution is adopted and applied to perform mutate operation in PSO. The development of a new dynamic mutation particle swarm optimization algorithm was established by the alpha-stable mutation. By dynamically modifying the stability coefficientof alpha-stable function, the amplitude and intension of the mutate operation is adjusted adaptively, and the global optimization ability of PSO is improved. The new algorithm is compared with DE and PSO on seven test functions . Simulation results show that the alpha-stable PSO algorithm have a faster convergence speed and a better global optimization performance in low, medium and high dimension problems. The proposed  algorithm is applied to drag reduction design of RAE2822 transonic airfoil and compared with PSO algorithm. The comparison results also show that our algorithm is more excellent than basic PSO.

Keyphrases: Dynamic Mutation, Particle Swarm Optimization, aerodynamic optimization, alpha-stable distribution

@booklet{EasyChair:45,
  author    = {Huayu Fan and Hao Zhan},
  title     = {A Fast PSO Algorithm Based on Alpha-stable Mutation and Its Application in Aerodynamic Optimization},
  doi       = {10.29007/v447},
  howpublished = {EasyChair Preprint 45},
  year      = {EasyChair, 2018}}