Stochastic model of production and inventory control using dynamic Bayesian network

Ji Sun Slim, Tae Hong Lee, Jin Il Kim, HeeHyol Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Bayesian Network is a stochastic model, which shows 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. This paper deals with the production and inventory control using the dynamic Bayesian network. The probabilistic values of the amount of delivered goods and the production quantities are changed in the real environment, and then the total stock is also changed randomly. The probabilistic distribution of the total stock is calculated through the propagation of the probability on the Bayesian network. Moreover, an adjusting rule of the production quantities to maintain the probability of the lower bound and the upper bound of the total stock to certain values is shown.

Original languageEnglish
Title of host publicationProceedings of the 13th International Symposium on Artificial Life and Robotics, AROB 13th'08
Pages405-410
Number of pages6
Publication statusPublished - 2008
Event13th International Symposium on Artificial Life and Robotics, AROB 13th'08 - Oita
Duration: 2008 Jan 312008 Feb 2

Other

Other13th International Symposium on Artificial Life and Robotics, AROB 13th'08
CityOita
Period08/1/3108/2/2

Fingerprint

Inventory control
Production control
Bayesian networks
Stochastic models
Random variables

Keywords

  • Dynamic Bayesian network
  • Graphical modeling
  • Probability distribution
  • Production inventory control

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Human-Computer Interaction

Cite this

Slim, J. S., Lee, T. H., Kim, J. I., & Lee, H. (2008). Stochastic model of production and inventory control using dynamic Bayesian network. In Proceedings of the 13th International Symposium on Artificial Life and Robotics, AROB 13th'08 (pp. 405-410)

Stochastic model of production and inventory control using dynamic Bayesian network. / Slim, Ji Sun; Lee, Tae Hong; Kim, Jin Il; Lee, HeeHyol.

Proceedings of the 13th International Symposium on Artificial Life and Robotics, AROB 13th'08. 2008. p. 405-410.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Slim, JS, Lee, TH, Kim, JI & Lee, H 2008, Stochastic model of production and inventory control using dynamic Bayesian network. in Proceedings of the 13th International Symposium on Artificial Life and Robotics, AROB 13th'08. pp. 405-410, 13th International Symposium on Artificial Life and Robotics, AROB 13th'08, Oita, 08/1/31.
Slim JS, Lee TH, Kim JI, Lee H. Stochastic model of production and inventory control using dynamic Bayesian network. In Proceedings of the 13th International Symposium on Artificial Life and Robotics, AROB 13th'08. 2008. p. 405-410
Slim, Ji Sun ; Lee, Tae Hong ; Kim, Jin Il ; Lee, HeeHyol. / Stochastic model of production and inventory control using dynamic Bayesian network. Proceedings of the 13th International Symposium on Artificial Life and Robotics, AROB 13th'08. 2008. pp. 405-410
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