[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(02):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(02):127-135.[doi:10.3969/j.issn.1673-4785.201309064]
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《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
第9卷
期数:
2014年02期
页码:
127-135
栏目:
出版日期:
2014-04-25

文章信息/Info

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 intelligenceartificial bee colony algorithmconstrained optimizationmulti-objective optimizationoptimization 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

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