Fuzzy knowledge-based approach to treating uncertainty in inventory control

Dobrila Petrovic, Edward Sweeney

Research output: Contribution to journalArticle

26 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 languageEnglish
Pages (from-to)147-152
Number of pages6
JournalComputer Integrated Manufacturing Systems
Volume7
Issue number3
DOIs
Publication statusPublished - Aug 1994

Fingerprint

Inventory control
Inventory Control
Knowledge-based
Fuzzy If-then Rules
Uncertainty
Uncertain Data
Imprecision
Probabilistic Approach
Fuzzy numbers
Manufacturing
Demand

Keywords

  • approximate reasoning
  • fuzzy set
  • inventory control
  • knowledge-based system

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering

Cite this

Fuzzy knowledge-based approach to treating uncertainty in inventory control. / Petrovic, Dobrila; Sweeney, Edward.

In: Computer Integrated Manufacturing Systems, Vol. 7, No. 3, 08.1994, p. 147-152.

Research output: Contribution to journalArticle

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