DocumentCode :
3228970
Title :
Job-shop scheduling problem with multiple process routes considering lot split and setup time
Author :
Shaotan, Xu ; Yu, Huang ; Chaoyong, Zhang ; Kunlei, Lian
Author_Institution :
State Key Lab. of Digital Manuf. Equip. & Technol., Huazhong Univ. of Sci. & Technol., Wuhan, China
fYear :
2010
fDate :
23-26 Sept. 2010
Firstpage :
421
Lastpage :
425
Abstract :
To improve production efficiency and reduce makespan, this paper investigates lot scheduling with multiple process routes in job shop. Equal sublots are adopted and integrated with parallel translation model to optimize production cycle. Based on improved genetic algorithm (GA), a novel initialization method is used for chromosome encoding rationally. Then a new crossover operation is proposed for the problem. The computation results show that the improved genetic algorithm is feasible and effective.
Keywords :
genetic algorithms; job shop scheduling; crossover operation; equal sublots; improved genetic algorithm; job-shop scheduling problem; lot split; multiple process routes; parallel translation model; production cycle optimization; setup time; genetic algorithm; job shop; lot streaming;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Bio-Inspired Computing: Theories and Applications (BIC-TA), 2010 IEEE Fifth International Conference on
Conference_Location :
Changsha
Print_ISBN :
978-1-4244-6437-1
Type :
conf
DOI :
10.1109/BICTA.2010.5645161
Filename :
5645161
Link To Document :
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