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Abstract
In this paper we proposes a new optimization algorithm—Bacterial Colony Optimization (BCO) which formulates the bacterial behavior model in a new way. The model is based on the principle of artificial bacterial behavior, including Chemotaxis, Communication, Elimination, Reproduction and Migration. The Chemotaxis and Communication are spread over the whole optimization process while other behaviors are implemented only when their relevant conditions are reached. Experiment results have proved a high efficiency searching capability of the new proposed artificial bacterial colony.
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Authors and Affiliations
College of Management, Shenzhen University, Shenzhen, 518060, China
Ben Niu & Hong Wang
Hefei Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei, 230031, China
Ben Niu
Institute for Cultural Industries, Shenzhen University, Shenzhen, 518060, China
Ben Niu
- Ben Niu
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Editors and Affiliations
Machine Learning and Systems Biology Laboratory, School of Electronics and Information Engineering, Tongji University, Shanghai, China
De-Shuang Huang
Department of Computer Science and Engineering, Indian Institute of Technology Kanpur, 208016, Kanpur, India
Phalguni Gupta
Department of Chemistry, University of Louisville, 2320 South Brook Street, 40292, Louisville, Kentucky, USA
Xiang Zhang
School of Electrical, Computer & Telecommunications Engineering, The University of Wollongong,, 2522, North Wollongong, NSW, Australia
Prashan Premaratne
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Niu, B., Wang, H. (2012). Bacterial Colony Optimization: Principles and Foundations. In: Huang, DS., Gupta, P., Zhang, X., Premaratne, P. (eds) Emerging Intelligent Computing Technology and Applications. ICIC 2012. Communications in Computer and Information Science, vol 304. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31837-5_73
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