Job shop scheduling in real-time cases

被引：10
|
作者：
Shugang, L [1 ]
Zhiming, W [1 ]
Xiaohong, P [1 ]
机构：
[1] Shanghai Jiao Tong Univ, Automat Dept, Shanghai 200030, Peoples R China
来源：
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY | 2005年 / 26卷 / 7-8期
关键词：
GA; job shop; neuro-fuzzy network; real-time scheduling;
D O I：
10.1007/s00170-003-2051-x
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
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.
引用
收藏
页码：870 / 875
页数：6
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