期刊
APPLIED SOFT COMPUTING
卷 41, 期 -, 页码 362-372出版社
ELSEVIER
DOI: 10.1016/j.asoc.2015.12.046
关键词
Artificial bee colony; Swarm intelligence; Bee memory; Foraging
资金
- National Natural Science Foundation of China [71001016, 71421001]
- Fundamental Research Funds for the Central Universities [DUT15RC(3)076, DUT15TD48]
- Humanity and Social Science Foundation of Ministry of Education of China [15YJCZH198]
- Economic and Social Development Foundation of Liaoning [2016lslktzizzx-01]
Artificial bee colony algorithm (ABC) is a new type of swarm intelligence methods which imitates the foraging behavior of honeybees. Due to its simple implementation with very small number of control parameters, many efforts have been done to explore ABC research in both algorithms and applications. In this paper, a new ABC variant named ABC with memory algorithm (ABCM) is described, which imitates a memory mechanism to the artificial bees to memorize their previous successful experiences of foraging behavior. The memory mechanism is applied to guide the further foraging of the artificial bees. Essentially, ABCM is inspired by the biological study of natural honeybees, rather than most of the other ABC variants that integrate existing algorithms into ABC framework. The superiority of ABCM is analyzed on a set of benchmark problems in comparison with ABC, quick ABC and several state-of-the-art algorithms. (C) 2016 Elsevier B.V. All rights reserved.
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