Abstract
Inventory control in complex manufacturing environments encounters various sources of uncertainty and imprecision. This paper presents one fuzzy knowledge-based approach to solving the problem of order quantity determination, in the presence of uncertain demand, lead time and actual inventory level. Uncertain data are represented by fuzzy numbers, and vaguely defined relations between them are modelled by fuzzy if-then rules. The proposed representation and inference mechanism are verified using a large number of examples. The results of three representative cases are summarized. Finally, a comparison between the developed fuzzy knowledge-based and traditional, probabilistic approaches is discussed.
| Original language | English |
|---|---|
| Pages (from-to) | 147-152 |
| Number of pages | 6 |
| Journal | Computer Integrated Manufacturing Systems |
| Volume | 7 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - Aug 1994 |
Keywords
- approximate reasoning
- fuzzy set
- inventory control
- knowledge-based system
ASJC Scopus subject areas
- Control and Systems Engineering
- Industrial and Manufacturing Engineering
Fingerprint Dive into the research topics of 'Fuzzy knowledge-based approach to treating uncertainty in inventory control'. Together they form a unique fingerprint.
Cite this
Petrovic, D., & Sweeney, E. (1994). Fuzzy knowledge-based approach to treating uncertainty in inventory control. Computer Integrated Manufacturing Systems, 7(3), 147-152. https://doi.org/10.1016/0951-5240(94)90033-7