A Dynamic Bayesian Network Model for production and inventory control
Ji-Sun Shin, Noriyuki Takazaki, Tae Hong Lee, Jin-Il Kim, Hee Hyol Lee · Electrical Engineering in Japan · 2011
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