A parallel Bees Algorithm implementation on GPU

Guo Heng Luo, Sheng Kai Huang, Yue Shan Chang, Shyan-Ming Yuan*

*Corresponding author for this work

Research output: Contribution to journalArticle

37 Scopus citations

Abstract

Bees Algorithm is a population-based method that is a computational bound algorithm whose inspired by the natural behavior of honey bees to finds a near-optimal solution for the search problem. Recently, many parallel swarm based algorithms have been developed for running on GPU (Graphic Processing Unit). Since nowadays developing a parallel Bee Algorithm running on the GPU becomes very important. In this paper, we extend the Bees Algorithm (CUBA (i.e. CUDA based Bees Algorithm)) in order to be run on the CUDA (Compute Unified Device Architecture). CUBA (CUDA based Bees Algorithm). We evaluate the performance of CUBA by conducting some experiments based on numerous famous optimization problems. Results show that CUBA significantly outperforms standard Bees Algorithm in numerous different optimization problems.

Original languageEnglish
Pages (from-to)271-279
Number of pages9
JournalJournal of Systems Architecture
Volume60
Issue number3
DOIs
StatePublished - 1 Mar 2014

Keywords

  • Bees Algorithm
  • CUDA
  • GPGPU
  • Parallel Bees Algorithm
  • Swarm intelligence

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