Artificial neural networks for real-time scheduling

被引：0

作者：

Nureldin, HM ^{[1
]}

O'Connor, RF ^{[1
]}

Duffill, AW ^{[1
]}

机构：

[1] Univ Birmingham, Sch Mfg & Mech Engn, Edgbaston, England

来源：

ADVANCES IN MANUFACTURING TECHNOLOGY XII | 1998年

关键词：

D O I：

暂无

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

In a real manufacturing environment, reactive scheduling takes place in realtime, not a predictable smooth one. Reactive scheduling is a complex process and it is possible to produce a large number of schedules for the same job. As a result many different models and practices have been introduced, by researchers, to generate the best or optimum schedules, with respect to a specific production situation. This paper presents artificial neural networks (ANN) as an alternative tool to provide a solution to the real-time scheduling issue. The initial work attempts to utilise the capability and performance of an ANN with the goal of developing a real-time reactive schedule and control system.

引用

页码：251 / 256

页数：4

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