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[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):127-135.[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(2):127-135.[doi:10.3969/j.issn.1673-4785.201309064]

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人工蜂群算法研究综述

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《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷: 9 期数: 2014年第2期页码: 127-135 栏目: 综述出版日期: 2014-04-25

Title:: Artificial bee colony algorithm: a survey

作者:: 秦全德¹, 程适², 李丽¹, 史玉回³; 1. 管理科学系深圳大学, 广东深圳 518060;
2. 宁波诺丁汉大学计算机科学系, 浙江宁波 315100;
3. 西交利物浦大学电气电子工程系, 江苏苏州 215123

Author(s):: QIN Quande¹, CHENG Shi², LI Li¹, SHI Yuhui³; 1. Department of Management Science, Shenzhen University, Shenzhen 518060, China;
2. Division of Computer Science, The University of Nottingham Ningbo, Ningbo 315100, China;
3. Department of Electrical and Electronics Engineering, Xi’an Jiaotong-Liverpool University, Suzhou 215123, China

关键词:: 群体智能; 人工蜂群算法; 约束优化; 多目标优化; 选择算法

Keywords:: swarm intelligence; artificial bee colony algorithm; constrained optimization; multi-objective optimization; optimization algorithm

分类号:: TP18;F062.3

DOI:: 10.3969/j.issn.1673-4785.201309064

摘要:: 作为一种较新的群体智能优化算法,人工蜂群算法自提出之时就受到学术界的广泛关注,目前已经在多个领域得到了成功应用。介绍了人工蜂群算法的生物背景和基本原理,在对基本人工蜂群算法的不足进行分析的基础上,归纳了当前人工蜂群算法的改进研究主要集中在算法的参数调整、混合算法和设计新的学习策略3个方面。针对现实的复杂环境,对人工蜂群算法在约束优化和多目标优化的研究进展进行了全面的综述。最后,阐述了人工蜂群算法的应用现状,并提出了人工蜂群算法有待进一步研究的问题。

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备注/Memo

收稿日期:2013-09-21。
基金项目:国家自然科学基金资助项目(71240015,61273367);广东高校优秀青年创新人才培养计划资助项目(2012WYM_0116);教育部人文社科青年基金资助项目(13YJC630123)
作者简介:程适,男,1983年生,博士,主要研究方向为演化计算、群体智能算法及其应用,数据挖掘与分析。
通讯作者:秦全德,男,1979年生,讲师,博士,主要研究仿向为智能计算及其应用、管理决策与优化。E-mail:qinquande@gmail.com.

更新日期/Last Update: 1900-01-01

人工蜂群算法研究综述 PDF下载HTML

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人工蜂群算法研究综述

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