Artificial Bee Colony Algorithm Based on Novel Mechanism for Fuzzy Portfolio Selection

doi:10.1109/TFUZZ.2018.2856120

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	Artificial Bee Colony Algorithm Based on Novel Mechanism for Fuzzy Portfolio Selection
	Gao, Weifeng 2; Sheng, Hailong 3; Wang, Jue1,4 ; Wang, Shouyang 1,4
刊名	IEEE TRANSACTIONS ON FUZZY SYSTEMS
	2019-05-01
卷号	27 期号:5 页码:966-978
关键词	Artificial bee colony algorithm (ABC) direction learning elite learning fuzzy portfolio selection search direction step size
ISSN号	1063-6706
DOI	10.1109/TFUZZ.2018.2856120
英文摘要	Although the introduction of fuzzy theory into a portfolio selection model can help improve the model's practicality, it would increase the difficulty of solving the model. To tackle the issue, this paper proposes a novel mechanism based artificial bee colony algorithm (ABC) consisting of two new proposed learning strategies-direction learning and elite learning. The direction learning strategy has a great potential to guide the search toward the promising areas. The elite learning strategy can gradually pick up the convergence rate without loss of the population diversity. The cooperation of the two approaches forms a mechanism, complementing each other to improve the performance of the algorithms. The proposed mechanism, named LL-mechanism, is introduced into three ABC variants-ABC, ghest-guided ABC (GABC), and CABC, generating LL-ABC, LL-GABC, and LL-CABC, respectively. The experimental results demonstrate the superior performance of the LL-mechanism and LL-CABC outperforms other methods in terms of solution quality, convergence rate, robustness, and numerical stability. Finally, the proposed LL-CABC approach is employed to solve the portfolio selection with fuzzy security return. The experiments on two portfolio selection models illustrate that LL-CABC is effective and promising for a fuzzy portfolio selection.
资助项目	National Nature Science Foundation of China[61772391] ; National Nature Science Foundation of China[61402534] ; National Nature Science Foundation of China[71771208] ; National Nature Science Foundation of China[71271202] ; Natural Science Basic Research Plan in Shaanxi Province of China[2018JQ6051] ; Natural Science Basic Research Plan in Shaanxi Province of China[2017JQ6059] ; Young Talent fund of University Association for Science and Technology in Shaanxi, China, Hong Kong Scholars Program
WOS研究方向	Computer Science ; Engineering
语种	英语
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号	WOS:000470836800012
内容类型	期刊论文
源URL	[http://ir.amss.ac.cn/handle/2S8OKBNM/34821]
专题	系统科学研究所
通讯作者	Wang, Jue
作者单位	1.Univ Chinese Acad Sci, Sch Econ & Management, Beijing 100190, Peoples R China 2.Xidian Univ, Sch Math & Stat, Xian 710126, Shaanxi, Peoples R China 3.China Univ Petr, Sch Sci, Qingdao 266580, Shandong, Peoples R China 4.Univ Chinese Acad Sci, Ctr Forecasting Sci, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Gao, Weifeng,Sheng, Hailong,Wang, Jue,et al. Artificial Bee Colony Algorithm Based on Novel Mechanism for Fuzzy Portfolio Selection[J]. IEEE TRANSACTIONS ON FUZZY SYSTEMS,2019,27(5):966-978.
APA	Gao, Weifeng,Sheng, Hailong,Wang, Jue,&Wang, Shouyang.(2019).Artificial Bee Colony Algorithm Based on Novel Mechanism for Fuzzy Portfolio Selection.IEEE TRANSACTIONS ON FUZZY SYSTEMS,27(5),966-978.
MLA	Gao, Weifeng,et al."Artificial Bee Colony Algorithm Based on Novel Mechanism for Fuzzy Portfolio Selection".IEEE TRANSACTIONS ON FUZZY SYSTEMS 27.5(2019):966-978.