Inventory models need information about the demand distribution. In practice, this information is not known with certainty and has to be estimated with often relatively few historical demand observations. Using these estimates leads to underperformance. This paper focuses on gamma distributed...

We address the problem of determining optimal ordering and pricing policies in a finite-horizon newsvendor model with unobservable lost sales. The demand distribution is price-dependent and involves unknown parameters. We consider both the cases of perishable and non-perishable inventory. A very...

The purpose of this paper is three fold: First, it demonstrates the non-convergence of the bisection method proposed in the literature for the trial-and-error implementation of the marginal-cost pricing in the absence of a demand function. Second, it provides a modified version of the bisection...

Awell-known result in the Bayesian inventory management literature is: If lost sales are not observed, the Bayesian optimal inventory level is larger than the myopic inventory level (one should "stock more" to learn about the demand distribution). This result has been proven in other studies...

This paper considers the periodic review inventory problem for which one or more parameters of the demand distribution are unknown with a known prior distribution chosen from the natural conjugate family. The Bayesian formulation of this problem results in a dynamic program with a...