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JACIII Vol.21 No.3 pp. 496-506
doi: 10.20965/jaciii.2017.p0496
(2017)

Paper:

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Characteristic Analysis of Artificial Bee Colony Algorithm with Network-Structure

Shunta Imamura*,†, Toshiya Kaihara*, Nobutada Fujii*, Daisuke Kokuryo*, and Akira Kitamura**

*Graduate School of System Informatics, Kobe University
1-1 Rokkodai-cho, Nada, Kobe, 657-8501 Hyogo, Japan

**Graduate School of Engineering, Tottori University
Koyama, Tottori 680-8552, Japan

†Corresponding author

Received:
February 26, 2016
Accepted:
January 16, 2017
Online released:
May 19, 2017
Published:
May 20, 2017
Creative Commons License
Keywords:
artificial bee colony algorithm, network-structure, swarm intelligence, high-dimensional problem
Abstract
The artificial bee colony (ABC) algorithm, which is inspired by the foraging behavior of honey bees, is one of the swarm intelligence systems. This algorithm can provide an efficient exploration of the optimal solutions using three different types of agents for optimization problems with multimodal functions. However, the performance of the conventional ABC algorithm decreases for high-dimensional problems. In this study, we propose an improved algorithm using the network structure of agents to enhance the ability for global search. The efficacy of the proposed algorithm is evaluated by performing computer experiments with high-dimensional benchmark functions.
Cite this article as:
S. Imamura, T. Kaihara, N. Fujii, D. Kokuryo, and A. Kitamura, “Characteristic Analysis of Artificial Bee Colony Algorithm with Network-Structure,” J. Adv. Comput. Intell. Intell. Inform., Vol.21 No.3, pp. 496-506, 2017.
Data files:
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Last updated on Apr. 18, 2024