A Dynamic Bayesian Network Model for production and inventory control

Ji Sun Shin, Noriyuki Takazaki, Tae Hong Lee, Jin Il Kim, Hee Hyol Lee

Research output: Contribution to journalArticle

Abstract

In general, production quantities and delivered goods change randomly and consequently total stocks also change randomly. This paper deals with production and inventory control using a Dynamic Bayesian Network. The Bayesian Network is a probabilistic model which represents the qualitative dependence between two or more random variables by a graph structure, and the quantitative relations between individual variables by conditional probabilities. The probabilistic distribution of the total stock is calculated by propagation of probabilities on the network. Furthermore, a rule for adjustment of production quantities maintains the desired probabilities of exceeding the lower and upper limits on total stocks.

Original languageEnglish
Pages (from-to)37-45
Number of pages9
JournalElectrical Engineering in Japan (English translation of Denki Gakkai Ronbunshi)
Volume175
Issue number2
DOIs
Publication statusPublished - 2011 Apr 30

Keywords

  • dynamic Bayesian network
  • graphical modeling
  • probabilistic distribution
  • production and inventory control

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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