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A Dynamic Bayesian Network Model for production and inventory control
Author(s) -
Shin JiSun,
Takazaki Noriyuki,
Lee TaeHong,
Kim JinIl,
Lee HeeHyol
Publication year - 2011
Publication title -
electrical engineering in japan
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.136
H-Index - 28
eISSN - 1520-6416
pISSN - 0424-7760
DOI - 10.1002/eej.21076
Subject(s) - probabilistic logic , bayesian network , bayesian probability , econometrics , production (economics) , conditional probability , computer science , mathematics , statistics , operations research , economics , macroeconomics
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. © 2011 Wiley Periodicals, Inc. Electr Eng Jpn, 175(2): 37–45, 2011; Published online in Wiley Online Library ( wileyonlinelibrary.com ). DOI 10.1002/eej.21076