[1]谭营,郑少秋.烟花算法研究进展[J].智能系统学报,2014,9(05):515-528.[doi:10.3969/j.issn.1673-4785.201409010]
 TAN Ying,ZHENG Shaoqiu.Recent advances in fireworks algorithm[J].CAAI Transactions on Intelligent Systems,2014,9(05):515-528.[doi:10.3969/j.issn.1673-4785.201409010]
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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05期
页码:
515-528
栏目:
出版日期:
2014-10-25

文章信息/Info

Title:
Recent advances in fireworks algorithm
作者:
谭营12 郑少秋12
1. 北京大学 机器感知与智能教育部重点实验室, 北京 100871;
2. 北京大学 信息科学与技术学院, 北京 100871
Author(s):
TAN Ying12 ZHENG Shaoqiu12
1. Key Laboratory of Machine Perception, Peking University, Beijing 100871, China;
2. School of Electronics Engineering and Computer Science, Peking University, Beijing 100871, China
关键词:
群体智能烟花算法爆炸半径自适应爆炸半径动态搜索机制多目标烟花算法并行实现
Keywords:
swarm intelligencefireworks algorithmexplosion amplitudeadaptive explosion amplitudedynamic search strategymulti-objective fireworks algorithmparallel implementation
分类号:
TP301
DOI:
10.3969/j.issn.1673-4785.201409010
摘要:
烟花算法由于具有很强的优化问题求解的能力,近年来逐渐受到研究者的广泛关注。对现有烟花算法的研究工作进行了全面总结,主要包括烟花算法提出的背景、烟花算法的基本原理、单目标烟花算法的改进、混合算法、多目标烟花算法、基于GPU的并行烟花算法以及烟花算法在实际问题中的应用研究等。对于单目标烟花算法及改进算法、混合算法,文中给出了各种改进烟花算法的机制分析和对比研究,最后,给出了烟花算法的未来研究方向,包括爆炸算子搜索机制的深入分析、烟花交互机制研究、多目标烟花算法研究、并行烟花算法研究、扩展烟花算法求解的问题类型以及应用拓展。
Abstract:
Fireworks algorithm (FWA) has shown great successes in dealing with complex optimization problems and has attracted a great amount of attention recently. In this paper, FWA was completely analyzed, Including the FWA background evaluation, the study of fundamental principles of FWA, developments in single objective FWA optimization, hybrid algorithms, multi-objective fireworks algorithm, graphic processing unit(GPU) based parallel fireworks algorithm, and their applications in practice. For single objective FWA and improved and hybrid algorithms, the mechanism analysis and comparative research of various improved FWAs are given in this paper. Finally, the future research directions for FWA are pointed out, which include the analysis of explosion operator, study of interaction strategies among the fireworks, research on multi-objective fireworks algorithm and parallel fireworks algorithm, types of solutions to the extended FWA, and application expansion.

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备注/Memo

备注/Memo:
收稿日期:2014-09-05。
基金项目:国家自然科学基金资助项目(61375119、61170057、60875080).
作者简介:郑少秋, 男, 1990年生, 博士研究生, 主要研究方向为群体智能、计算智能、模式识别。
通讯作者:谭营, 男, 1964年生, 教授, 博士生导师, 博士, 主要研究方向为计算智能、群体智能、机器学习方法、人工免疫系统、群体智能、智能信息处理及信息安全应用。担任IJCIPR主编, IEEETransonCybernetics副主编, IJSIR副主编等, IEEESeniorMember, IEEECIS-ETTC委员, ICSI系列会议大会主席等。主持国家"863"计划、国家自然科学基金、国际合作交流等科研项目30余项。获得2009年度国家自然科学二等奖, 是中科院百人计划入选者。获国家发明专利授权3项, 发表学术论文260余篇, 出版专著5部。E-mail:ytan@pku.edu.cn.
更新日期/Last Update: 1900-01-01