BFO with Information Communicational System Based on Different Topologies Structure

Bacterial foraging optimization (BFO) is a swarm intelligent algorithm which draws inspiration from the foraging behavior of Escherichia coli. This paper improves BFO by introduced information communicational system in which bacteria share information according to neighbor topologies to slow down the premature convergence. The effects of full connected topology, ring topology, star topology and Von Neumann topology on the BFO are systematically investigated, and the new BFO algorithms are named as BFO-FC, BFO-R, BFO-S, and BFO-VM, respectively. Experimental results on four benchmark functions validate the effectiveness of the proposed algorithms.

[1]  Zhen Ji,et al.  A Fast Bacterial Swarming Algorithm for high-dimensional function optimization , 2008, 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence).

[2]  J. Kennedy,et al.  Population structure and particle swarm performance , 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).

[3]  Ben Niu,et al.  Bacterial foraging based approaches to portfolio optimization with liquidity risk , 2012, Neurocomputing.

[4]  Kevin M. Passino,et al.  Biomimicry of bacterial foraging for distributed optimization and control , 2002 .

[5]  Yunlong Zhu,et al.  RFID Networks Planning Using Evolutionary Algorithms and Swarm Intelligence , 2008, 2008 4th International Conference on Wireless Communications, Networking and Mobile Computing.

[6]  Dong Hwa Kim Hybrid GA-BF based intelligent PID controller tuning for AVR system , 2011, Appl. Soft Comput..

[7]  Kevin D. Seppi,et al.  An exploration of topologies and communication in large particle swarms , 2009, 2009 IEEE Congress on Evolutionary Computation.

[8]  Hong Wang,et al.  Bacterial Colony Optimization , 2012 .