A note on lead time and distributional assumptions in continuous review inventory models
Computers and Operations Research
Computers and Operations Research
Mixtures of Truncated Exponentials in Hybrid Bayesian Networks
ECSQARU '01 Proceedings of the 6th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Improved inventory models with service level and lead time
Computers and Operations Research
Computers and Operations Research
Learning hybrid Bayesian networks using mixtures of truncated exponentials
International Journal of Approximate Reasoning
Mixtures of truncated basis functions
International Journal of Approximate Reasoning
Optimal production planning under diffusion demand pattern
Mathematical and Computer Modelling: An International Journal
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This paper examines optimal policies in a continuous review inventory management system when demand in each time period follows a log-normal distribution. In this scenario, the distribution for demand during the entire lead time period has no known form. The proposed procedure uses the Fenton-Wilkinson method to estimate the parameters for a single log-normal distribution that approximates the probability density function (PDF) for lead time demand, conditional on a specific lead time. Once these parameters are determined, a mixture of truncated exponentials (MTE) function that approximates the lead time demand distribution is constructed. The objective is to include the log-normal distribution in a robust decision support system where the PDF that best fits the historical period demand data is used to construct the lead time demand distribution. Experimental results indicate that when the log-normal distribution is the best fit, the model presented in this paper reduces expected inventory costs by improving optimal policies, as compared to other potential approximations.