DocumentCode
441987
Title
Solving the job shop scheduling problem by an immune algorithm
Author
Zuo, Xing-quan ; Fan, Yu-shun
Author_Institution
Dept. of Autom., Tsinghua Univ., Beijing, China
Volume
6
fYear
2005
fDate
18-21 Aug. 2005
Firstpage
3282
Abstract
An immune algorithm is presented for solving the job shop scheduling problem. In the algorithm, the niche technology is used to keep the diversity of the population and chaos variables are employed to perform antibody mutation. The code of an antibody is based on random keys, and a heuristic process is given to decode the antibody into a parameterized active schedule to reduce the solution space. Experimental results demonstrate the algorithm is effective for solving job shop problems.
Keywords
evolutionary computation; job shop scheduling; optimisation; evolutionary algorithm; heuristic process; immune algorithm; job shop scheduling problem; optimization computation; random key; Artificial neural networks; Computer networks; Delay effects; Genetic mutations; Immune system; Job shop scheduling; Optimal scheduling; Processor scheduling; Scheduling algorithm; Space technology; Job shop scheduling; evolutionary algorithm; immune algorithm; optimization computation;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on
Conference_Location
Guangzhou, China
Print_ISBN
0-7803-9091-1
Type
conf
DOI
10.1109/ICMLC.2005.1527509
Filename
1527509
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