Article ID: | iaor20022108 |
Country: | United Kingdom |
Volume: | 29 |
Issue: | 4 |
Start Page Number: | 403 |
End Page Number: | 422 |
Publication Date: | Apr 2002 |
Journal: | Computers and Operations Research |
Authors: | Pakkala T.P.M., Kamath K. Rajashree |
Keywords: | programming: dynamic |
In this paper, the Bayesian approach to demand estimation is outlined for the cases of stationary as well as non-stationary demand. The optimal policy is derived for an inventory model that allows stock disposal, and is shown to be the solution of a dynamic programming backward recursion. Then, a method is given to search for the optimal order level around the myopic order level. Finally, a numerical study is performed to make a profit comparison between the Bayesian and non-Bayesian approaches, when the demand follows a stationary lognormal distribution. A profit comparison is also made between the stationary and non-stationary Bayesian approaches to observe whether the Bayesian approach incorporates non-stationarity in the demand. And, it is observed whether stock disposal reduces the losses due to ignoring non-stationarity in the demand.