TOWARDS AN ADAPTIVE KANBAN SYSTEM

被引:13
作者
CHAUDHURY, A
WHINSTON, AB
机构
[1] University of Texas, Austin, TX
[2] Institute, University of Texas, Austin, TX
关键词
D O I
10.1080/00207549008942729
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This paper presents a control methodology for flow shops that is decentralized and adaptive in nature, and has low data handling and computational requirements. The methodology is based on stochastic automata methods for modelling learning behaviour. It is proposed that such a methodology can be used with Kanban type control technique to make flow shop systems more flexible and adaptive in nature, Relationship of the control model to computational models such as neural computing is discussed. © 1990 Taylor & Francis Group, LLC.
引用
收藏
页码:437 / 458
页数:22
相关论文
共 35 条
[21]  
Narendra K.S., Wheeler R.M., Learning models for decentralized decisionmaking, Automatica, 21, pp. 479-484, (1985)
[22]  
Narendra K.S., Thatcher M., Learning automata: A survey, IEEE Transaction on Systems, Man and Cybernetics, 4, pp. 323-334, (1974)
[23]  
Narendra K.S., Viswanathan R.S., A two-level system of stochastic automata for periodic random environment, IEEE Transaction on Systems, Man and Cybernetics, 2, pp. 285-289, (1972)
[24]  
Parunak H., Kindrick J., Irish B., Material handling: A conservative domain for neural connectivity and propagation, Proceedings of the Sixth National Conference on Artificial Intelligence, pp. 307-311, (1987)
[25]  
Parunak H., Distributed artificial intelligence, Artificial Intelligence, (1988)
[26]  
Rumelhart D.E., McClelland J.L., Parallel Distributed Processing, (1986)
[27]  
Shapiro I.J., Narendra K.S., Use of stochastic automata for parameter selfoptimization with multi-model performance criteria, IEEE Transaction on Systems, Man and Cybernetics, 5, pp. 109-114, (1969)
[28]  
Shaw M., Whinston A.B., Automatic planning and flexible scheduling: A knowledge-based approach, Proceedings of IEEE Conference on Automation and Robotics, pp. 890-894, (1985)
[29]  
Stankovic J.A., Simulation of three adaptive, decentralized controlled task scheduling algorithms, Computer Networks, 8, pp. 199-217, (1984)
[30]  
Stankovic J.A., Stability and distributed scheduling algorithms, IEEE Transaction on Software Engineering, 11, pp. 1141-1152, (1985)