DocumentCode :
2989911
Title :
A Modified Genetic Algorithm to Due Date of Job Shop Scheduling Problem
Author :
Zhu, Chuanjun ; Chen, Yurong ; Zhang, Chaoyong
Author_Institution :
Dept. of Mech. Eng., Hubei Automotive Ind. Inst., Shiyan, China
fYear :
2009
fDate :
18-20 Jan. 2009
Firstpage :
1
Lastpage :
5
Abstract :
This paper presents a modified genetic search algorithm for the non-regular job-shop scheduling problem with due date. The chromosome representation of the problem is based on the operation-based representation. In order to reduce the search space, the procedure for generating active schedules is constructed. For avoiding premature convergence in the conventional genetic algorithms (GA), the precedence operation crossover (POX) and approach of the generation alteration model are presented. The algorithm is tested on the instances for due date, the computation results validate the effectiveness of the proposed algorithm.
Keywords :
genetic algorithms; job shop scheduling; search problems; chromosome representation; conventional genetic algorithms; modified genetic search algorithm; nonregular job shop scheduling problem; operation-based representation; precedence operation crossover; Automotive engineering; Biological cells; Biological system modeling; Computational modeling; Encoding; Evolution (biology); Genetic algorithms; Job shop scheduling; Processor scheduling; Scheduling algorithm;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Network and Multimedia Technology, 2009. CNMT 2009. International Symposium on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-5272-9
Type :
conf
DOI :
10.1109/CNMT.2009.5374722
Filename :
5374722
Link To Document :
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