Job shop scheduling in real-time cases |
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Authors: | Li Shugang Wu Zhiming Pang Xiaohong |
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Affiliation: | (1) Automation Department, Shanghai Jiaotong University, 1954 Huashan Road, Shanghai, 200030, P.R. China |
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Abstract: | A real-time scheduling algorithm is proposed, that is, to first make a fuzzy classification for the operations of jobs in
real-time and then, according to their fuzzy sort, to schedule them with the heuristic. The heuristic is obtained by training
a neural network offline with the genetic algorithm. Based on these ideas a real-time scheduler is built with neuro-fuzzy
network (NFN). Finally the simulation for the real-time scheduling and the rescheduling are made. The results show that the
real-time scheduling algorithm is effective and highly efficient compared to the first in and first out (FIFO) and the Lagrangian
relaxation (LR) method. |
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Keywords: | GA Job shop Neuro-fuzzy network Real-time scheduling |
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