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Discrete Dynamics in Nature and Society
Volume 2012 (2012), Article ID 698057, 28 pages
http://dx.doi.org/10.1155/2012/698057
Research Article

Bacterial Colony Optimization

Ben Niu1,2 and Hong Wang1

1College of Management, Shenzhen University, Shenzhen 518060, China
2Hefei Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei 230031, China

Received 27 May 2012; Accepted 24 August 2012

Academic Editor: Binggen Zhang

Copyright © 2012 Ben Niu and Hong Wang. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

This paper investigates the behaviors at different developmental stages in Escherichia coli (E. coli) lifecycle and developing a new biologically inspired optimization algorithm named bacterial colony optimization (BCO). BCO is based on a lifecycle model that simulates some typical behaviors of E. coli bacteria during their whole lifecycle, including chemotaxis, communication, elimination, reproduction, and migration. A newly created chemotaxis strategy combined with communication mechanism is developed to simplify the bacterial optimization, which is spread over the whole optimization process. However, the other behaviors such as elimination, reproduction, and migration are implemented only when the given conditions are satisfied. Two types of interactive communication schemas: individuals exchange schema and group exchange schema are designed to improve the optimization efficiency. In the simulation studies, a set of 12 benchmark functions belonging to three classes (unimodal, multimodal, and rotated problems) are performed, and the performances of the proposed algorithms are compared with five recent evolutionary algorithms to demonstrate the superiority of BCO.