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Bacterial Foraging Optimization

Bacterial Foraging Optimization

Kevin M. Passino
Copyright: © 2012 |Pages: 16
ISBN13: 9781466615922|ISBN10: 1466615923|EISBN13: 9781466615939
DOI: 10.4018/978-1-4666-1592-2.ch013
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MLA

Passino, Kevin M. "Bacterial Foraging Optimization." Innovations and Developments of Swarm Intelligence Applications, edited by Yuhui Shi, IGI Global, 2012, pp. 219-234. https://doi.org/10.4018/978-1-4666-1592-2.ch013

APA

Passino, K. M. (2012). Bacterial Foraging Optimization. In Y. Shi (Ed.), Innovations and Developments of Swarm Intelligence Applications (pp. 219-234). IGI Global. https://doi.org/10.4018/978-1-4666-1592-2.ch013

Chicago

Passino, Kevin M. "Bacterial Foraging Optimization." In Innovations and Developments of Swarm Intelligence Applications, edited by Yuhui Shi, 219-234. Hershey, PA: IGI Global, 2012. https://doi.org/10.4018/978-1-4666-1592-2.ch013

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Abstract

The bacterial foraging optimization (BFO) algorithm mimics how bacteria forage over a landscape of nutrients to perform parallel nongradient optimization. In this article, the author provides a tutorial on BFO, including an overview of the biology of bacterial foraging and the pseudo-code that models this process. The algorithms features are briefly compared to those in genetic algorithms, other bio-inspired methods, and nongradient optimization. The applications and future directions of BFO are also presented.

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