DocumentCode :
3378241
Title :
Cooperative Bacterial Foraging Optimization
Author :
Shao, Yichuan ; Chen, HanNing
Author_Institution :
Coll. of Inf. Sci. & Eng., Shenyang Univ., Shenyang, China
fYear :
2009
fDate :
13-14 Dec. 2009
Firstpage :
486
Lastpage :
488
Abstract :
Bacterial Foraging Optimization (BFO) is a novel optimization algorithm based on the social foraging behavior of E. coli bacteria. However, the original BFO algorithm possesses a poor convergence behavior compared to the other successful nature-inspired algorithms. This paper presents a variation on the original BFO algorithm, namely the Cooperative Bacterial Foraging Optimization (CBFO). The cooperative approaches used here resulted in a significant improvement in the performance of the original BFO algorithm in terms of convergence speed, accuracy and robustness. The experiments compare the performance of two variants of CBFO with the original BFO, the standard PSO and a real-coded GA on a set of 4 widely-used benchmark functions. The proposed new method shows a marked improvement in performance over the original BFO and appears to be comparable with the PSO and GA.
Keywords :
artificial life; convergence; microorganisms; optimisation; E. coli bacteria; convergence; cooperative bacterial foraging optimization; nature-inspired algorithm; social foraging behavior; Automation; Biomedical engineering; Convergence; Educational institutions; Information science; Machine learning algorithms; Microorganisms; Optimization methods; Robustness; Space exploration; Bacterial Foraging Optimization; Cooperative Bacterial Foraging Optimization; GA; PSO;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
BioMedical Information Engineering, 2009. FBIE 2009. International Conference on Future
Conference_Location :
Sanya
Print_ISBN :
978-1-4244-4690-2
Electronic_ISBN :
978-1-4244-4692-6
Type :
conf
DOI :
10.1109/FBIE.2009.5405806
Filename :
5405806
Link To Document :
بازگشت