A novel artificial bee colony based on Gaussian sampling. (19th May 2017)

• Record Type: Journal Article
• Authors: You, Xuemei; Ma, Yinghong; Liu, Zhiyuan
• Is Part Of: Journal of discrete mathematical sciences & cryptography. Volume 20:Number 4(2017)
• Page Start: 957
• Page End: 970
• Publication Date: 2017-05-19
• Subjects: Artificial bee colony -- Swarm intelligence -- Gaussian sampling -- Search strategy -- Global optimization; Computer science -- Mathematics -- Periodicals; Cryptography -- Periodicals; Computer science -- Mathematics; Cryptography; Periodicals; 004.0151
• DOI: 10.1080/09720529.2017.1359379
• Languages: English
• ISSNs: 0972-0529

Abstract

Abstract: Artificial bee colony (ABC) is an efficient optimization tool, which is inspired by swarm intelligence. Recent studies show that ABC is competitive to other famous bio-inspired optimization algorithms. However, ABC is good at global search, but poor at local search. To overcome this problem, a new ABC variant based on Gaussian sampling is proposed. Experiments are carried out on ten well-known benchmark functions. Computational results show that our approach outperforms the standard ABC and two other improved ABC algorithms.