Fuzzy knowledge-based approach to treating uncertainty in inventory control

Dobrila Petrovic; Edward Sweeney

doi:10.1016/0951-5240(94)90033-7

Fuzzy knowledge-based approach to treating uncertainty in inventory control

Dobrila Petrovic, Edward Sweeney

School of Computing, Electronics and Maths

Research output: Contribution to journal › Article › peer-review

27 Citations (Scopus)

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	https://doi.org/10.1016/0951-5240(94)90033-7
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

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