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Fuzzy knowledge-based approach to treating uncertainty in inventory control

  • Dobrila Petrovic
  • , Edward Sweeney
    • University of Belgrade
    • University of Warwick

    Research output: Contribution to journalArticlepeer-review

    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

    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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