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Differential Operators Embedded Artificial Bee Colony Algorithm

Differential Operators Embedded Artificial Bee Colony Algorithm

Tarun Kumar Sharma, Millie Pant
Copyright: © 2011 |Volume: 2 |Issue: 3 |Pages: 14
ISSN: 1942-3594|EISSN: 1942-3608|EISBN13: 9781613505557|DOI: 10.4018/jaec.2011070101
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MLA

Sharma, Tarun Kumar, and Millie Pant. "Differential Operators Embedded Artificial Bee Colony Algorithm." IJAEC vol.2, no.3 2011: pp.1-14. http://doi.org/10.4018/jaec.2011070101

APA

Sharma, T. K. & Pant, M. (2011). Differential Operators Embedded Artificial Bee Colony Algorithm. International Journal of Applied Evolutionary Computation (IJAEC), 2(3), 1-14. http://doi.org/10.4018/jaec.2011070101

Chicago

Sharma, Tarun Kumar, and Millie Pant. "Differential Operators Embedded Artificial Bee Colony Algorithm," International Journal of Applied Evolutionary Computation (IJAEC) 2, no.3: 1-14. http://doi.org/10.4018/jaec.2011070101

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Abstract

Artificial Bee Colony (ABC) is one of the most recent nature inspired (NIA) algorithms based on swarming metaphor. Proposed by Karaboga in 2005, ABC has proven to be a robust and efficient algorithm for solving global optimization problems over continuous space. However, it has been observed that the structure of ABC is such that it supports exploration more in comparison to exploitation. In order to maintain a balance between these two antagonist factors, this paper suggests incorporation of differential evolution (DE) operators in the structure of basic ABC algorithm. The proposed algorithm called DE-ABC is validated on a set of 10 benchmark problems and the numerical results are compared with basic DE and basic ABC algorithm. The numerical results indicate that the presence of DE operators help in a significant improvement in the performance of ABC algorithm.

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