[1]刘永波.投资组合优化的可行性规则人工蜂群算法[J].智能系统学报,2014,9(4):491-498.[doi:10.3969/j.issn.1673-4785.201308047]
 LIU Yongbo.An artificial bee colony algorithm with the feasibility rulefor portfolio investment optimizations[J].CAAI Transactions on Intelligent Systems,2014,9(4):491-498.[doi:10.3969/j.issn.1673-4785.201308047]
点击复制

投资组合优化的可行性规则人工蜂群算法

参考文献/References:
[1] 张伟, 周群, 孙德宝. 遗传算法求解最佳证券组合[J]. 数量经济技术经济研究, 2001(10): 114-116.ZHANG Wei, ZHOU Qun, SUN Debao. Genetic algorithm for portfolio investment optimizations[J]. Quantitative and Technical Economics, 2001(10): 114-116.
[2] 何洋林, 叶春明, 徐济东. 基于改进AGA算法求解含交易费用组合投资模型[J]. 计算机工程与应用, 2007, 43(11): 235-237.HE Yanglin, YE Chunming, XU Jidong. Portfolio investment model including transaction fee and solution based on adaptive genetic algorithm[J]. Computer Engineering and Applications, 2007, 43(11): 235-237.
[3] SOLEIMANI H, GOLMAKANI H R, SALIMI M H. Markowitz-based portfolio selection with minimum transaction lots, cardinality constraints and regarding sector capitalization using genetic algorithm[J]. Expert Systems with Applications, 2009, 36(3): 5058-5063.
[4] 夏梦雨, 叶春明, 徐济东. 用微粒群算法求解含交易费用的组合投资模型[J]. 上海理工大学学报, 2008, 30(4): 379-381, 386.XIA Mengyu, YE Chunming, XU Jidong. Solution of portfolio investment model including transaction fee with particle swarm algorithm[J]. Journal of University of Shanghai for Science and Technology, 2008, 30(4): 379-381, 386.
[5] 刘晓峰, 陈通, 张连营. 基于微粒群算法的最佳证券投资组合研究[J]. 系统管理学报, 2008, 17(2): 221-224, 234.LIU Xiaofeng, CHEN Tong, ZHANG Lianying. Study on the portfolio problem based on particle swarm optimization[J]. Journal of Systems and Management, 2008, 17(2): 221-224, 234.
[6] 刘衍民, 赵庆祯, 牛奔. 约束粒子群算法求解自融资投资组合模型研究[J]. 数学的实践与认识, 2011, 41(2): 78-84.LIU Yanmin, ZHAO Qingzhen, NIU Ben. Constrain particle swarm optimizer for solving self-financing portfolio model[J]. Mathematics in Practice and Theory, 2011, 41(2): 78-84.
[7] 李磊, 程晨, 张颖. 基于文化算法的投资组合规划问题求解[J]. 江南大学学报: 自然科学版, 2009, 8(1): 108-111.LI Lei, CHENG Chen, ZHANG Ying. Solving portfolio programming problem based on cultural algorithm[J]. Journal of Jiangnan University: Natural Science Edition, 2009, 8(1): 108-111.
[8] 江家宝, 尤振燕, 孙俊. 基于微分进化算法的多阶段投资组合优化[J]. 计算机工程与应用, 2007, 43(3): 189-193.JIANG Jiabao, YOU Zhenyan, SUN Jun. Multi-stage portfolio optimization using differentiation evolution algorithms[J]. Computer Engineering and Applications, 2007, 43(3): 189-193.
[9] 李国成, 肖庆宪. 基数约束投资组合问题的一种混合元启发式算法求解[J]. 计算机应用研究, 2013, (8): 2292-2297.LI Guocheng, XIAO Qingxian. Hybrid meta-heuristic algorithm for solving cardinality constrained portfolio optimization[J]. Application Research of Computers, 2013, 30(8): 2292-2297.
[10] LWIN K, QU R. A hybrid algorithm for constrained portfolio selection problems[J]. Applied Intelligence, 2013, 39(2): 251-266.
[11] PONSICH A, JAIMES A L, COELLO C A. A survey on multiobjective evolutionary algorithms for the solution of the portfolio optimization problem and other finance and economics applications[J]. IEEE Transactions on Evolutionary Computation, 2013, 17(3): 321-344.
[12] BRANKE J, SCHECKENBACH B, STEIN M, et al. Portfolio optimization with an envelope-based multi-objective evolutionary optimization[J]. European Journal on Operations Research, 2009, 199(3): 684-693.
[13] KARABOGA D, BASTURK B. A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm[J]. Journal of Global Optimization, 2007, 39(3): 459-471.
[14] KARABOGA D, BASTURK B. On the performance of artificial bee colony (ABC) algorithm[J]. Applied Soft Computing, 2008, 8(1): 687-697.
[15] 段海滨, 张祥银, 徐春芳. 仿生智能计算[M]. 北京: 科学出版社, 2011: 88-106.DUAN Haibin, ZHANG Xiangyin, XU Chunfang. Bio-inspired Computing[M]. Beijing: Science Press, 2011: 88-106.
[16] MALLIPEDDI R, SUGANTHAN P N. Ensemble of constraint handling techniques[J]. IEEE Transactions on Evolutionary Computation, 2010, 14(4): 561-579.
[17] 温涛, 盛国军, 郭权, 等. 基于改进粒子群算法的Web服务组合[J]. 计算机学报, 2013, 36(5): 1031-1046.WEN Tao, SHENG Guojun, GUO Quan, et al. Web service composition based on modified particle swarm optimization[J]. Chinese Journal of Computers, 2013, 36(5): 1031-1046.
[18] 张文修, 梁怡. 遗传算法的数学基础[M]. 2版. 西安: 西安交通大学出版社, 2003: 118-122.
[19] 宁爱平, 张雪英. 人工蜂群算法的收敛性分析[J]. 控制与决策, 2013, 28(9): 1554-1558.NING Aiping, ZHANG Xueying. Convergence analysis of artificial bee colony algorithm[J]. Control and Decision, 2013, 28(9): 1554-1558.
[20] 车林仙. 面向机构分析与设计的差分进化算法研究[D]. 徐州: 中国矿业大学, 2012: 21-30.CHE Linxian. Study on differential evolution algorithms orientating analysis and design of mechanisms[D]. Xuzhou: China University of Mining and Technology, 2012: 21-30.
[21] ZHANG Xiangyin, DUAN Haibin, YU Yaxiang. Receding horizon control for multi-UAVs close formation control based on differential evolution[J]. Science China Information Sciences, 2010, 53(2): 223-235.
相似文献/References:
[1]秦全德,程适,李丽,等.人工蜂群算法研究综述[J].智能系统学报,2014,9(2):127.[doi:10.3969/j.issn.1673-4785.201309064]
 QIN Quande,CHENG Shi,LI Li,et al.Artificial bee colony algorithm: a survey[J].CAAI Transactions on Intelligent Systems,2014,9():127.[doi:10.3969/j.issn.1673-4785.201309064]

备注/Memo

收稿日期:2013-08-29。
通讯作者:刘永波,男,1973年生,讲师,主要研究方向为计算机软件。主持青年基金项目1个、主研社科联课题2个,发表学术论文8篇,合作出版教材2部。E-mail: yongbo_liu@126.com

更新日期/Last Update: 1900-01-01
Copyright © 《 智能系统学报》 编辑部
地址:(150001)黑龙江省哈尔滨市南岗区南通大街145-1号楼 电话:0451- 82534001、82518134 邮箱:tis@vip.sina.com