DocumentCode
2858889
Title
Energy adaptive immune genetic algorithm for collaborative design task scheduling in Cloud Manufacturing system
Author
Laili, Yuanjun ; Zhang, Lin ; Tao, Fei
Author_Institution
Sch. of Autom. Scicence & Electr. Eng., Beihang Univ., Beijing, China
fYear
2011
fDate
6-9 Dec. 2011
Firstpage
1912
Lastpage
1916
Abstract
A new manufacturing paradigm, i.e. Cloud Manufacturing (CMfg) has been proposed recently. In order to satisfy high efficiency and low cost collaborative design task scheduling in CMfg, a new energy adaptive immune genetic algorithm (EAIGA) was designed. With the introduction of potential energy storage and detection, the new algorithm can not only improve searching diversity based on immune strategy, but also adaptively adjust the probabilities of crossover and mutation with low time complexity. The experimental results demonstrate that the new algorithm can effectively solving collaborative design task scheduling problem with a good balance between searching diversification and intensification.
Keywords
computational complexity; design for manufacture; genetic algorithms; manufacturing systems; probability; scheduling; cloud manufacturing system; collaborative design task scheduling; crossover probability; energy adaptive immune genetic algorithm; energy detection; energy storage; mutation probability; time complexity; Algorithm design and analysis; Collaboration; Genetic algorithms; Immune system; Job shop scheduling; Potential energy; Collaborative design task scheduling; adaptive immune genetic algorithm;
fLanguage
English
Publisher
ieee
Conference_Titel
Industrial Engineering and Engineering Management (IEEM), 2011 IEEE International Conference on
Conference_Location
Singapore
ISSN
2157-3611
Print_ISBN
978-1-4577-0740-7
Electronic_ISBN
2157-3611
Type
conf
DOI
10.1109/IEEM.2011.6118248
Filename
6118248
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