A Dynamic Bayesian Network model for the production and inventory control

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

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


In general, the production quantities and delivered goods are changed randomly and then the total stock is also changed randomly. This paper deals with the production and inventory control using the Dynamic Bayesian Network. Bayesian Network is a probabilistic model which represents the qualitative dependence between two or more random variables by the graph structure, and indicates the quantitative relations between individual variables by the conditional probability. The probabilistic distribution of the total stock is calculated through the propagation of the probability on the network. Moreover, an adjusting rule of the production quantities to maintain the probability of a lower limit and a ceiling of the total stock to certain values is shown.

Original languageEnglish
Pages (from-to)1789-1796+10
JournalIEEJ Transactions on Electronics, Information and Systems
Issue number12
Publication statusPublished - 2008
Externally publishedYes


  • Dynamic Bayesian Network
  • Graphical modeling
  • Probabilistic distribution
  • Production and inventory control

ASJC Scopus subject areas

  • Electrical and Electronic Engineering


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