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An adaptive immune genetic algorithm and its application
Shi G(石刚); Ma J(马佳); Jing YW(井元伟)
Department工业信息学研究室
Conference Name2009 3rd International Conference on Teaching and Computational Science, WTCS 2009
Conference DateDecember 19-20, 2009
Conference PlaceShenzhen, China
Source PublicationAdvances in Intelligent and Soft Computing
PublisherSPRINGER-VERLAG
Publication PlaceBERLIN
2009
Pages373-380
Indexed ByEI ; CPCI(ISTP)
EI Accession number20122115051000
WOS IDWOS:000310856800048
Contribution Rank1
ISSN1867-5662
ISBN978-3-642-11276-8
KeywordFlexible Job-shop Scheduling Problem Immune Genetic Algorithm Immune Operator Adaptive Strategyvaccine
AbstractTo avoid premature and guarantee the diversity of the population, an adaptive immune genetic algorithm(AIGA) is proposed to solve these problems. In this method, the AIGA flow structure is presented via combining the immune regulating mechanism and the genetic algorithm. Experimental results showed that the proposed AIGA can rise above efficiently such difficulties of SGA as precocious convergence and poor local search ability and provide well the global converging ability to enhance both global convergency and convergence rate, thus solving effectively the flexible job-shop scheduling problem (FJSP). © 2012 Springer-Verlag Berlin Heidelberg.
Language英语
Citation statistics
Document Type会议论文
Identifierhttp://ir.sia.cn/handle/173321/8318
Collection工业信息学研究室
Corresponding AuthorShi G(石刚)
Affiliation1.School of Information Science and Engineering, Northeastern University, Shenyang, China
2.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China
Recommended Citation
GB/T 7714
Shi G,Ma J,Jing YW. An adaptive immune genetic algorithm and its application[C]. BERLIN:SPRINGER-VERLAG,2009:373-380.
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