中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页 机构 成果 学者
  
  1. CAS IR Grid
  2. 数学与系统科学研究院
  3. 中国科学院数学与系统科学研究院
  4. 系统科学研究所
Artificial Bee Colony Algorithm Based on Novel Mechanism for Fuzzy Portfolio Selection

文献类型：期刊论文

作者Gao, Weifeng2; Sheng, Hailong3; Wang, Jue1,4; Wang, Shouyang1,4
刊名IEEE TRANSACTIONS ON FUZZY SYSTEMS
出版日期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
DOI10.1109/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
WOS记录号WOS:000470836800012
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
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.

入库方式： OAI收割

来源：数学与系统科学研究院

浏览0
下载0
收藏0
其他版本

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。