An efficient genetic algorithm for job-shop scheduling problems with fuzzy processing time and fuzzy duedate

1999 ◽  
Vol 36 (2) ◽  
pp. 325-341 ◽  
Author(s):  
Masatoshi Sakawa ◽  
Tetsuya Mori
2012 ◽  
Vol 217-219 ◽  
pp. 1444-1448
Author(s):  
Xiang Ke Tian ◽  
Jian Wang

The job-shop scheduling problem (JSP), which is one of the best-known machine scheduling problems, is among the hardest combinatorial optimization problems. In this paper, the key technology of building simulation model in Plant Simulation is researched and also the build-in genetic algorithm of optimizing module is used to optimize job-shop scheduling, which can assure the scientific decision. At last, an example is used to illustrate the optimization process of the Job-Shop scheduling problem with Plant Simulation genetic algorithm modules.


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