Production adjusting method based on the predicted distribution of production and inventory using a dynamic Bayesian network

Yeong Hwa Park*, Ji Sun Shin, Ki Yun Woo, Fumihiro Shoji, Hee Hyol Lee

*この研究の対応する著者

研究成果: Article査読

1 被引用数 (Scopus)

抄録

In general, production quantities and goods delivered are changed randomly, and then the total stock is also changed randomly. This article deals with the production and inventory control of an automobile production parts line using a dynamic Bayesian network. A Bayesian network indicates the quantitative relations between individual variables by conditional probability. The probabilistic distribution of the total stock is calculated through the propagation of the probability on the network. Moreover, an adjusting rule for the production quantities to maintain the probability of the lower and upper bound values of the total stock at certain values is shown.

本文言語English
ページ(範囲)138-143
ページ数6
ジャーナルArtificial Life and Robotics
14
2
DOI
出版ステータスPublished - 2009 11 1

ASJC Scopus subject areas

  • 生化学、遺伝学、分子生物学(全般)
  • 人工知能

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