Biologically Adaptive Artificial Bee Colony for Numerical Optimization

被引：1

作者：

Hsieh, Sheng-Ta ^{[1
]}

Cheng, Hao-Wen ^{[2
]}

Lin, Chun-Ling ^{[3
]}

Sun, Tsung-Ying ^{[2
]}

机构：

[1] Oriental Inst Technol, Dept Commun Engn, New Taipei, Taiwan

[2] Natl Dong Hwa Univ, Dept Elect Engn, Hualien, Taiwan

[3] Ming Chi Univ Technol, Dept Elect Engn, New Taipei, Taiwan

来源：

2017 FIFTH INTERNATIONAL SYMPOSIUM ON COMPUTING AND NETWORKING (CANDAR) | 2017年

关键词：

artificial bee colony; numerical optimization; adaptive; Halton sequence;

D O I：

10.1109/CANDAR.2017.94

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

The artificial bee colony (ABC) algorithm is a wellknown algorithm for solving numerical optimal problems. In this paper, a biologically adaptive artificial bee colony (BAABC) algorithm is proposed. In BAABC, the initialization of population is performed by the Halton Sequence so the population is generated in potential solution space. Besides, the size of population is varying according to status of solution searching. If BAABC finds a good solution, the size of population is increased for enhancing solution searching and vice versa. To examine the proposed method, fifteen evaluated functions are adopted in experiments. The result shows that BAABC performs better than related ABC methods on most of the test function.

引用

页码：187 / 193

页数：7

共 10 条

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Lin, Chun-Ling
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