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Applied Computational Intelligence and Soft Computing
Volume 2012, Article ID 907853, 7 pages
Research Article

A Crossover Bacterial Foraging Optimization Algorithm

Department of Electronics and Telecommunication Engineering, VSS University of Technology, Burla 768018, India

Received 16 April 2012; Revised 11 July 2012; Accepted 9 August 2012

Academic Editor: Jun He

Copyright © 2012 Rutuparna Panda and Manoj Kumar Naik. 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.


This paper presents a modified bacterial foraging optimization algorithm called crossover bacterial foraging optimization algorithm, which inherits the crossover technique of genetic algorithm. This can be used for improvising the evaluation of optimal objective function values. The idea of using crossover mechanism is to search nearby locations by offspring (50 percent of bacteria), because they are randomly produced at different locations. In the traditional bacterial foraging optimization algorithm, search starts from the same locations (50 percent of bacteria are replicated) which is not desirable. Seven different benchmark functions are considered for performance evaluation. Also, comparison with the results of previous methods is presented to reveal the effectiveness of the proposed algorithm.