Abstract
In this paper we investigate about the Neighborhood search mechanisms to improve the performance of Artificial Bee Colony (ABC) on shifted and rotated benchmark functions, proposed in CEC 2005. Although basic version of ABC has been provided with adaptive search mechanism, it will not be able to tackle complex functions with much accuracy unless it was enriched with an efficient neighborhood search scheme. Experimental results have explicitly shown that Neighborhood search based ABC (NS-ABC) performed superiorly well over other variants of ABC.
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Rajasekhar, A., Das, S., Panigrahi, B.K., Mallick, M.K. (2012). Neighborhood Search Based Artificial Bee Colony Algorithm for Numerical Function Optimization. In: Panigrahi, B.K., Das, S., Suganthan, P.N., Nanda, P.K. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2012. Lecture Notes in Computer Science, vol 7677. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35380-2_28
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DOI: https://doi.org/10.1007/978-3-642-35380-2_28
Publisher Name: Springer, Berlin, Heidelberg
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