An adaptive artificial fish swarm algorithm with elimination and clone mechanism
Yao Zhenghua1,2, Ren Zihui1
COMPUTER MODELLING & NEW TECHNOLOGIES 2014 18(12A) 110-116
1 School of Information and Electrical Engineering China University of Mining and Technology, 221116, Xuzhou, Jiangsu Province, China
2 School of Mechanical and Electrical Engineering, Yang Zi Normal University, 408000, Chongqing, China
For the problem with imprecise optimal solution and reduced convergence efficiency of basic artificial fish swarm algorithm in the late, the adaptive functions of artificial fish’s view and step were used to improve fish algorithm. On this basis, with the new concept of effective artificial fish proposed, the elimination and clone mechanism was used to increase the number of effective fish to solve the problem with artificial fish individuals scattered and the algorithm convergence efficiency dropped. The experimental results showed that the elimination and clone mechanism enabled the artificial fish to aggregate to the global optimum rapidly, which improved the algorithm convergence efficiency and stability. Finally, the comparative studies were carried on simulation among the basic artificial fish swarm algorithm (BAFSA), adaptive artificial fish swarm algorithm (AAFSA), basic artificial fish swarm algorithm with elimination and clone mechanism (ECAFSA) and the adaptive artificial fish swarm algorithm with elimination and clone mechanism (ECAAFSA). Simulation results showed that, the elimination and clone mechanism could increase the number of effective artificial fish significantly, which improved the convergence efficiency and stability of the algorithm