DocumentCode
2673872
Title
Solving fuzzy job-shop scheduling problem by genetic algorithm
Author
Li, Junqing ; Xie, Shengxian ; Sun, Tao ; Wang, Yuting ; Yang, Huaqing
Author_Institution
Sch. of Comput., Liaocheng Univ., Liaocheng, China
fYear
2012
fDate
23-25 May 2012
Firstpage
3243
Lastpage
3247
Abstract
In this study, we propose a genetic algorithm for solving the job-shop scheduling problem with fuzzy makespan. The solution in the proposed algorithm is represented by a string of discrete values. The crossover and mutation operators are designed to make the proposed algorithm with high quality exploration and exploitation capability. Experimental results on several random generated cases verified the efficiency and effectiveness of the proposed algorithm.
Keywords
fuzzy set theory; genetic algorithms; job shop scheduling; crossover operator; discrete values string; exploitation capability; exploration capability; fuzzy job-shop scheduling problem; fuzzy makespan; genetic algorithm; mutation operator; Algorithm design and analysis; Computers; Educational institutions; Genetic algorithms; Job shop scheduling; Process control; Fuzzy processing time; Genetic algorithm; Job shop scheduling problem;
fLanguage
English
Publisher
ieee
Conference_Titel
Control and Decision Conference (CCDC), 2012 24th Chinese
Conference_Location
Taiyuan
Print_ISBN
978-1-4577-2073-4
Type
conf
DOI
10.1109/CCDC.2012.6244513
Filename
6244513
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