Population structure and particle swarm performance
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Population structure and particle swarm performance
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
An exploration of topologies and communication in large particle swarms
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Hybrid GA-BF based intelligent PID controller tuning for AVR system
Applied Soft Computing
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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.