DocumentCode :
3351516
Title :
A batch splitting job shop scheduling problem with bounded batch sizes under multiple-resource constraints using genetic algorithm
Author :
Hai-Yan Wang ; Yan-Wei Zhao ; Xin-li Xu ; Wan-Liang Wang
Author_Institution :
Key Lab. of Mech. Manuf. & Autom. of Minist. of Educ., Zhejiang Univ. of Technol., Hangzhou
fYear :
2008
fDate :
21-24 Sept. 2008
Firstpage :
220
Lastpage :
225
Abstract :
Considering alternative resources for operations, requirement of multiple resources to process an operation and a jobpsilas batch size greater than one in the real manufacturing environment, a study is made on the batch splitting scheduling problem with bounded batch sizes under multiple-resource constraints, based on the objective to minimize the maximum completion time. A genetic algorithm which is suitable for this problem is proposed, with a new chromosome representation, which takes into account the batch splitting of the original batches of jobs. And a new crossover method and a new mutation method are proposed based on the new chromosome representation. The results of the simulation indicate that the method is feasible and efficient.
Keywords :
batch processing (industrial); fuzzy set theory; genetic algorithms; job shop scheduling; batch splitting; fuzzy processing time; genetic algorithm; job shop scheduling; multiple-resource constraints; Biological cells; Educational institutions; Educational technology; Fuzzy logic; Genetic algorithms; Genetic mutations; Job shop scheduling; Manufacturing automation; Manufacturing processes; Manufacturing systems; batch splitting scheduling; fuzzy processing time; genetic algorithm; multiple-resource constraints;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cybernetics and Intelligent Systems, 2008 IEEE Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-1673-8
Electronic_ISBN :
978-1-4244-1674-5
Type :
conf
DOI :
10.1109/ICCIS.2008.4670883
Filename :
4670883
Link To Document :
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