DocumentCode
2320038
Title
Immune genetic algorithm for flexible job-shop scheduling problem
Author
Ma, Jia ; Zhu, Yunlong ; Shi, Gang
Author_Institution
Shenyang Inst. of Autom., Chinese Acad. of Sci., Shenyang, China
fYear
2010
fDate
16-20 Aug. 2010
Firstpage
486
Lastpage
489
Abstract
An kind of immune genetic algorithm(IGA) is proposed for solving the flexible job-shop scheduling problem(FJSP). Based on the globalsearching method of classic genetic algorithm (SG), and using the diversity preservation strategy of antibodies in biology immunity mechanism, the method greatly improves the colony diversity of GA and compared to genetic algorithm. The results show that immune genetic algorithm performs better in aspect of global and local search ability and search speed.
Keywords
genetic algorithms; job shop scheduling; search problems; biology immunity mechanism; colony diversity; diversity preservation strategy; flexible job-shop scheduling problem; global searching method; immune genetic algorithm; Immune system; Job shop scheduling; Planning; Processor scheduling; Turning; Vaccines; FJSP; immune genetic algorithm; immune operator; resource constrained;
fLanguage
English
Publisher
ieee
Conference_Titel
Automation and Logistics (ICAL), 2010 IEEE International Conference on
Conference_Location
Hong Kong and Macau
Print_ISBN
978-1-4244-8375-4
Electronic_ISBN
978-1-4244-8374-7
Type
conf
DOI
10.1109/ICAL.2010.5585331
Filename
5585331
Link To Document