Abstract
Artificial bee colony (ABC) algorithm has been widely used to solve the optimization problems. In the existing ABC algorithms, choosing which employed bee giving up its food source only based on its current trial number. It may cause some promising areas are exploited insufficiently and some non-significant areas are searched excessively. Thus, much more searching resources are wasted. To cope with this problem, an improved exhausted food source identification mechanism based on space partitioning (ISP) is designed, which considers the food source states both in the objective space and searching space simultaneously. Then, the proposed mechanism is applied to the basic ABC algorithm and a recently improved ABC algorithm. The experimental results have demonstrated that the ABC algorithms with the designed exhausted food source identification mechanism perform better than the original ABC algorithms in almost all the functions on the CEC2015 test suit.
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This work is funded by Shenyang Dongda Emerging Industrial Technology Research Institute.
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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Ning, J., Zhao, H., Sun, P., Feng, Y., Zhao, T. (2019). An Improved Exhausted-Food-Sources-Identification Mechanism for the Artificial Bee Colony Algorithm. In: Song, H., Jiang, D. (eds) Simulation Tools and Techniques. SIMUtools 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 295. Springer, Cham. https://doi.org/10.1007/978-3-030-32216-8_62
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DOI: https://doi.org/10.1007/978-3-030-32216-8_62
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