Abstract
In this paper, a hybrid between Bat algorithm (BA) and Artificial Bee Colony (ABC) with a communication strategy is proposed for solving numerical optimization problems. The several worst individual of Bats in BA will be replaced with the better artificial agents in ABC algorithm after running every Ri iterations, and on the contrary, the poorer agents of ABC will be replacing with the better individual of BA. The proposed communication strategy provides the information flow for the bats to communicate in Bat algorithm with the agents in ABC algorithm. Four benchmark functions are used to test the behavior of convergence, the accuracy, and the speed of the proposed method. The results show that the proposed increases the convergence and accuracy more than original BA is up to 78% and original ABC is at 11% on finding the near best solution improvement.
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Nguyen, TT., Pan, JS., Dao, TK., Kuo, MY., Horng, MF. (2014). Hybrid Bat Algorithm with Artificial Bee Colony. In: Pan, JS., Snasel, V., Corchado, E., Abraham, A., Wang, SL. (eds) Intelligent Data analysis and its Applications, Volume II. Advances in Intelligent Systems and Computing, vol 298. Springer, Cham. https://doi.org/10.1007/978-3-319-07773-4_5
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DOI: https://doi.org/10.1007/978-3-319-07773-4_5
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-07772-7
Online ISBN: 978-3-319-07773-4
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