We consider a joint pricing and inventory control problem in which the customer's response to selling price and the demand distribution are not known a priori. Unsatisfied demand is lost and unobserved, and the only available information for decision-making is the observed sales data (a.k.a....

We consider a periodic-review single-product inventory system with fixed cost under censored demand. Under full demand distributional information, it is well-known that the celebrated $(s,S)$ policy is optimal. In this paper, we assume the firm does not know the demand distribution a priori, and...

Optimizing the treatment regimen is a crucial medical decision-making problem. This can be thought of as a two-dimensional decision-making problem with a nested structure, because it involves determining the optimal medication along with its optimal dose. In many cases, it is a challenge to...

We propose the first learning algorithm for single-product, periodic-review, backlogging inventory systems with random production capacity. Different than the existing literature on this class of problems, we assume that the firm has neither prior information about the demand distribution nor...

Hospitals are typically uncertain about the readmission impact of a care unit placement decision for a patient. The placement decision is challenging due to the wide variety of patient characteristics, uncertain needs of patients, and the limited number of beds in critical and intermediate care...