An artificial bee colony algorithm with a distance factor
by Min Zhou; Runxiu Wu; Hui Sun
International Journal of Computing Science and Mathematics (IJCSM), Vol. 16, No. 4, 2022

Abstract: Aiming at the shortcomings of standard artificial bee colony (ABC) algorithms, such as weak local searching ability, poor diversity and easy to fall into local optimum, we propose the ABC algorithm with distance factor (DF_ABC). With the current optimal honey source as the reference, the new algorithm introduces the honey source distance reflecting the difference in the honey source location, and defines the distance factor controlling the searching direction of the algorithm through the honey source distance. The proposed searching strategy is capable of self-adaption. When the honey source distance is large, the particle can quickly jump to the peak (valley) where the global optimal point is located with the peak (valley) jumping ability; when the distance is small, the location information of the optimal honey source is used for local searching to speed up the algorithm convergence. The effectiveness of the proposed searching strategy is verified by the results of the experiment on benchmark test functions. Compared with other improved algorithms, the proposed algorithm showcases the best comprehensive performance.

Online publication date: Wed, 01-Feb-2023

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