A crossover bacterial foraging optimization algorithm

Authors:
Rutuparna Panda;Manoj Kumar Naik
Affiliations:
Department of Electronics and Telecommunication Engineering, VSS University of Technology, Burla, India;Department of Electronics and Telecommunication Engineering, VSS University of Technology, Burla, India
Venue:
Applied Computational Intelligence and Soft Computing
Year:
2012

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Abstract

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 crossovermechanism 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.