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The Bees Algorithm and Its Applications

The Bees Algorithm and Its Applications

Baris Yuce, Ernesto Mastrocinque, Michael S. Packianather, Alfredo Lambiase, Duc Truong Pham
ISBN13: 9781466672581|ISBN10: 1466672587|EISBN13: 9781466672598
DOI: 10.4018/978-1-4666-7258-1.ch004
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MLA

Yuce, Baris, et al. "The Bees Algorithm and Its Applications." Handbook of Research on Artificial Intelligence Techniques and Algorithms, edited by Pandian Vasant, IGI Global, 2015, pp. 122-151. https://doi.org/10.4018/978-1-4666-7258-1.ch004

APA

Yuce, B., Mastrocinque, E., Packianather, M. S., Lambiase, A., & Pham, D. T. (2015). The Bees Algorithm and Its Applications. In P. Vasant (Ed.), Handbook of Research on Artificial Intelligence Techniques and Algorithms (pp. 122-151). IGI Global. https://doi.org/10.4018/978-1-4666-7258-1.ch004

Chicago

Yuce, Baris, et al. "The Bees Algorithm and Its Applications." In Handbook of Research on Artificial Intelligence Techniques and Algorithms, edited by Pandian Vasant, 122-151. Hershey, PA: IGI Global, 2015. https://doi.org/10.4018/978-1-4666-7258-1.ch004

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Abstract

The Bees Algorithm (BA) is a swarm-based optimization algorithm inspired by the food foraging behavior of honeybees. The aim of this chapter is to describe a swarm-based optimization algorithm called the Bees Algorithm and its applications to real world problems. After an explanation of the natural foraging behavior of honeybees, the basic Bees Algorithm and its enhanced version based on Adaptive Neighborhood Search and Site Abandonment (ANSSA) strategy are described and two applications are discussed in detail. The first application deals with the optimization of several benchmark functions and the results obtained by the ANSSA-based BA is compared with the basic BA and other optimization algorithms. The second application deals with the multi-objective optimization problem in finding the best supply chain configuration.

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