• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

J4 ›› 2016, Vol. 38 ›› Issue (06): 1164-1170.

• 论文 • Previous Articles     Next Articles

An adaptive FA algorithm based on global information sharing  

LU Kezhong1,2,SUN Jun3   

  1. (1.Department of Computer Science,Chizhou University,Chizhou 247100;
    2.Hefei National Laboratory for Physical Sciences at the Microscale,University of Science and Technology of China,Hefei 230026;
     3.School of IoT Engineering,Jiangnan University,Wuxi 214021,China)
  • Received:2015-04-20 Revised:2015-06-18 Online:2016-06-25 Published:2016-06-25

Abstract:

The firefly algorithm (FA) for high dimensional problems has some disadvantages, including slow convergence speed, low solving precision and unsatisfactory optimization effect. To overcome these disadvantages, we propose a novel adaptive FA algorithm based on global information sharing. Firstly, an adaptive control for gamma value is designed by the swarm distance. Secondly, the search process information of the firefly algorithm is updated to enhance its adjustment capacity of refinement. Thirdly, the global searching ability is improved by introducing the Delta potential well of the vector subspace based on the global mean location information. Simulation results show that the proposal has better convergence speed and precision than the basic FA and the PSO.

Key words: firefly algorithm;adaptive;global information sharing;process information update