doi:

DOI: 10.3724/SP.J.1087.2013.03380

Journal of Computer Applications (计算机应用) 2013/33:12 PP.3380-3384

Artificial fish swarm parallel algorithm based on multi-core cluster


Abstract:
Concerning the problems of low accuracy, limitations of stagnation and slow convergence speed in the later evolution process of Artificial Fish Swarm Algorithm (AFSA), a Parallel Dynamic weigh Niches Artificial Fish Swarm (PDN-AFS) algorithm based on multi-core cluster was proposed. Firstly, the advantages and disadvantages of AFSA were analyzed, and dynamic weighting factor strategy and niche mechanism were adopted, hence a new Dynamic weigh Niches Artificial Fish Swarm (DN-AFS) algorithm was put forward. Then parallel design and analysis of DN-AFS algorithm based on parallel programming model (MPI+OpenMP) were introduced. Finally, the simulation experiments on multi-core cluster environment were given. The experimental results show that PDN-AFS can effectively improve the convergence speed and optimization performance of the complex multimodal function optimization problem, and achieve high speed ratio.

Key words:Artificial Fish Swarm Algorithm (AFSA),dynamic weighting factor,niche,parallel algorithm,MPI+OpenMP

ReleaseDate:2014-07-21 16:59:22



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