Title: Multivariate Markov chain models for production planning
Author: Dong-Mei Zhu, Wai-Ki Ching
Advanced Modeling and Applied Computing Laboratory, Department of Mathematics, The University of Hong Kong, Pokfulam Road, Hong Kong.
Advanced Modeling and Applied Computing Laboratory, Department of Mathematics, The University of Hong Kong, Pokfulam Road, Hong Kong
Abstract: Markov models are commonly used in modelling many practical systems such as queueing networks, manufacturing systems and inventory systems. In this paper, we consider a multivariate Markov chain model for modelling multiple categorical data sequences. We develop new efficient estimation methods for the model parameters. We then apply the model and methods to demand predictions and production planning for a soft-drink company in Hong Kong. This problem is essentially a newsboy's problem in a multivariate Markov chain framework. Numerical examples are given to demonstrate the effectiveness of the proposed methods.
Keywords: multivariate Markov chain models; categorical data sequences; demand prediction; newsboy problem; production planning; Hong Kong; soft drinks industry.
Int. J. of Intelligent Engineering Informatics, 2011 Vol.1, No.2, pp.156 - 173
Available online: 19 May 2011