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JACIII Vol.26 No.1 pp. 23-27
doi: 10.20965/jaciii.2022.p0023
(2022)

Paper:

A Culture-Based Artificial Bee Colony Algorithm for Optimization in Dynamic Environments

Dongli Jia*,**

*School of Information and Electronic Engineering, Hebei University of Engineering
No.19 Taiji Road, Handan, Hebei 056038, China

**Hebei Key Laboratory of Security & Protection Information Sensing and Processing
No.19 Taiji Road, Handan, Hebei 056038, China

Received:
October 4, 2019
Accepted:
October 11, 2021
Published:
January 20, 2022
Keywords:
dynamic optimization, artificial bee colony, cultural algorithm
Abstract

A novel culture-based multiswarm artificial bee colony (CMABC) algorithm was proposed to address dynamic optimization problems. The historical experience of sub-swarms is preserved as cultural knowledge to guide the subsequent evolutionary process. Experiments were conducted on the moving peaks benchmark function. The results show that the CMABC algorithm was better than, or at least comparable to, the basic ABC algorithm, and other state-of-the-art algorithms.

Cite this article as:
D. Jia, “A Culture-Based Artificial Bee Colony Algorithm for Optimization in Dynamic Environments,” J. Adv. Comput. Intell. Intell. Inform., Vol.26, No.1, pp. 23-27, 2022.
Data files:
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Last updated on Sep. 27, 2022