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Production Markovian Inventory Model with Bayes Estimation

Journal of Supply Chain Management Systems

Volume 7 Issue 3

Published: 2018
Author(s) Name: N. S. Indhumathy, P. R. Jayashree | Author(s) Affiliation: Research Scholar, Department of Statistics, Presidency College, Chennai, Tamil Nadu, India.
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Abstract

A Markovian inventory periodic review production model with inter-demand time as exponential distribution is considered in this paper. The model is developed on the basis of constant production rate and constant rate of deteriorating items without shortages. The unit production cost is inversely proportional to the demand rate. The model contains the exponential parameter which is unknown and is estimated through MLE and Baye’s under a squared error loss function. The conjugate Gamma prior is used as the prior distribution of exponential distribution. Finally, a numerical MCMC simulation is used to compare the estimators obtained with Expected risk and are shown graphically. The objective of the paper is to develop an optimum policy that minimizes the total average cost by using the above estimates of the parameter. The sensitivity analysis is also carried out for the model with percentage change in the parameters.

Keywords: Bayes Estimation, Deteriorating Items, Exponential Distribution, Optimal Time Periods, Squared Loss Function, Stochastic Demand

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