[1]杨蒙蒙,王水花,陈 燚,等.生物地理学优化算法与应用综述[J].南京师范大学学报(工程技术版),2018,18(02):050.[doi:10.3969/j.issn.1672-1292.2018.02.007]
　Yang Mengmeng,Wang Shuihua,Chen Yi,et al.Survey of Algorithms and Applications ofBiogeography-based Optimization[J].Journal of Nanjing Normal University(Engineering and Technology),2018,18(02):050.[doi:10.3969/j.issn.1672-1292.2018.02.007]
点击复制

生物地理学优化算法与应用综述
分享到：

南京师范大学学报（工程技术版）[ISSN:1006-6977/CN:61-1281/TN]

卷:
18卷
期数:
2018年02期
页码:
050
栏目:
计算机与信息工程
出版日期:
2018-06-30

文章信息/Info

Title:
Survey of Algorithms and Applications ofBiogeography-based Optimization
文章编号:
1672-1292(2018)02-0050-06
作者:
杨蒙蒙1; 王水花1; 陈 燚1; 张煜东1; 2
(1.南京师范大学计算机科学与技术学院,江苏 南京 210023)(2.莱斯特大学信息学院,莱斯特 LEI 7RH)
Author(s):
Yang Mengmeng1; Wang Shuihua1; Chen Yi1; Zhang Yudong1; 2
(1.School of Computer Science and Technology,Nanjing Normal University,Nanjing 210023,China)(2.Department of Informatics,University of Leicester,Leicester LEI 7RH,United Kingdom)
关键词:
生物地理学优化; 算法; 应用; 综述
Keywords:
biogeography-based optimization; algorithm; application; survey
分类号:
TP301.6
DOI:
10.3969/j.issn.1672-1292.2018.02.007
文献标志码:
A
摘要:
从生物地理学优化(biogeography-based optimization,BBO)算法的背景出发,详细介绍BBO算法的产生和发展,阐述了BBO算法的基本思想、突变操作、迁移操作以及算法流程,将BBO算法与几种先进的优化算法对比并总结,探讨了算法应用的拓展,并讨论了BBO的优化改进算法.
Abstract:
Biogeography-based optimization(BBO)is a novel optimization algorithm based on biogeography theory which was proposed by Dan Simon in 2008. Firstly,based on the background of BBO algorithm,the paper introduces the creation and the development of BBO in detail. In addition,the basic idea of the BBO,mutation operation,migration operation,and pseudo-code of the algorithm are explained. Secondly,we summarize the comparison between BBO algorithm and several state-of-the-art optimization algorithms. Thirdly,we discuss the applications of BBO algorithm. And finally,we focus on the improvement of BBO algorithms.

参考文献/References:

[1] DAN S. Biogeography-based optimization[J]. Evolutionary computation IEEE transactions on,2008,12(6):702-713.
[2]MARCO DORIGO,THOMAS STUTZLE. 蚁群优化[M]. 北京:清华大学出版社,2007.MARCO DORIGO,THOMAS STUTZLE. Ant colony optimization[M]. Beijing:Tsinghua University Press,2007.(in Chinese)
[3]KENNEDY J,EBERHART R. Particle swarm optimization[C]//IEEE International Conference on Neural Networks. New York:IEEE,1995:215-218.
[4]VENTER G,SOBIESZCZANSKISOBIESKI J. Particle swarm optimization[J]. AIAA journal,2013,41(8):129-132.
[5]WANG D,TAN D,LIU L. Particle swarm optimization algorithm:an overview[J]. Soft computing,2018,22(2):387-408.
[6]周现甫. 遗传算法的原理及应用[J]. 科技展望,2017,27(3):265.
ZHOU X F. Principles and applications of genetic algorithms[J]. Science and technology,2017,27(3):265.(in Chinese)
[7]葛继科,邱玉辉,吴春明,等. 遗传算法研究综述[J]. 计算机应用研究,2008,25(10):2911-2916.
GE J K,QIU Y H,WU C M,et al. Summary of genetic algorithms research[J]. Application research of computers,2008,25(10):2911-2916.(in Chinese)
[8]MADRASWALA H S,DESHPANDE A S. Genetic algorithm solution to unit commitment problem[C]//IEEE International Conference on Power Electronics,Intelligent Control and Energy Systems. Delhi,India:IEEE,2016:4-11.
[9]XING B,GAO W J. Biogeography-based Optimization Algorithm[M]. Switzerland:Springer International Publishing,2014.
[10]DAS S,SUGANTHAN P N. Differential evolution:a survey of the state-of-the-art[J]. IEEE transactions on evolutionary computation,2011,15(1):4-31.
[11]PRICE K,STORN R M,LAMPINEN J A. Differential evolution:a practical approach to global optimization(natural computing series)[M]. New York:Springer-Verlag,2005.
[12]STORN R,PRICE K. Differential evolution—a simple and efficient heuristic for global optimization over continuous spaces[M]. Netherlands:Kluwer Academic Publishers,1997.
[13]HALIM Z,UZMA. Optimizing the minimum spanning tree-based extracted clusters using evolution strategy[J]. Cluster computing,2017,20:1-15[2017-12-20]. https://doi.org/10.1007/s10586-017-0868-6.
[14]MA H. An analysis of the equilibrium of migration models for biogeography-based optimization[J]. Information sciences,2010,180(18):3444-3464.
[15]YAO X,LIU Y,LIN G. Evolutionary programming made faster[J]. IEEE transactions on evolutionary computation,2002,3(2):82-102.
[16]ZHANG Y,PHILLIPS P,WANG S,et al. Fruit classification by biogeography-based optimization and feed forward neural network[J]. Expert systems,2016,33(3):239-253.
[17]YANG G,ZHANG Y,YANG J,et al. Automated classification of brain images using wavelet-energy and biogeography-based optimization[J]. Multimedia tools and applications,2016,75(23):15601-15617.
[18]BANSAL J C,FARSWAN P. Wind farm layout using biogeography based optimization[J]. Renewable energy,2017,107:386-402.
[19]BHATTACHARYA A,CHATTOPADHYAY P K. Biogeography-based optimization for different economic load dispatch problems[J]. IEEE transactions on power systems,2010,25(2):1064-1077.
[20]HADIDI A,NAZARI A. Design and economic optimization of shell-and-tube heat exchangers using biogeography-based(BBO)algorithm[J]. Applied thermal engineering,2013,51(1):1263-1272.
[21]BACKHURST J R. Coulson and Richardson’s chemical engineering[J]. Butterworth-Heinemann,2009(154):665.
[22]HADIDI A. A robust approach for optimal design of plate fin heat exchangers using biogeography based optimization(BBO)algorithm[J]. Applied energy,2015,150:196-210.
[23]BANSAL J C,FARSWAN P. A novel disruption in biogeography-based optimization with application to optimal power flow problem[J]. Applied intelligence,2016,46:1-26.
[24]ZHANG Y,WANG S,DONG Z,et al. Pathological brain detection in magnetic resonance imaging scanning by wavelet entropy and hybridization of biogeography-based optimization and particle swarm optimization[J]. Progress in electromagnetics research,2015,152:41-58.
[25]MA H P,SIMON D. Blended biogeography-based optimization for constrained optimization[J]. Eng Appl Artif Intell,2011,24(3):517-525.
[26]ZHANG Y,WU X,LU S,et al. Smart detection on abnormal breasts in digital mammography based on contrast-limited adaptive histogram equalization and chaotic adaptive real-coded biogeography-based optimization[J]. Simulation,2016,92(9):873-885.
[27]GONG W,CAI Z,LING C X. DE/BBO:a hybrid differential evolution with biogeography-based optimization for global numerical optimization[J]. Soft computing,2010,15(4):645-665.
[28]WANG S,LI P,CHEN P,et al. Pathological brain detection via wavelet packet tsallis entropy and real-coded biogeography-based optimization[J]. Fundamenta informaticae,2017,151(1):275-291.

备注/Memo

备注/Memo:
收稿日期:2017-09-20.
基金项目:国家自然科学基金(61602250)、江苏省自然科学基金(BK20150983).
通讯联系人:张煜东,教授,博士生导师,研究方向:人工智能与医学图像处理. E-mail:yudongzhang@ieee.org
更新日期/Last Update: 2018-06-30