We study in this paper an online matching problem where a central platform needs to match a number of limited resources to different groups of users that arrive sequentially over time. The reward of each matching option depends both on the type of resource and the time period the user arrives....

We consider a stylistic question of dynamic pricing of a single product with demand learning. The candidate prices belong to a wide range of price interval, and the modeling of the demand functions is nonparametric in nature, imposing only smoothness regularity conditions. One important aspect...

This paper investigates the impact of pre-existing offline data on online learning, in the context of dynamic pricing. We study a single-product dynamic pricing problem over a selling horizon of T periods. The demand in each period is determined by the price of the product according to a linear...

This paper develops a multi-attribute competition model for procurement of short life cycle products. In such an environment, the buyer installs dedicated production capacity at the suppliers before the demand is realized. Final production orders are decided after demand materializes. Of course,...

Multi-armed bandit has been well-known for its efficiency in online decision-making in terms of minimizing the loss of the participants' welfare during experiments (i.e., the regret). In clinical trials and many other scenarios, the statistical power of inferring the treatment effects (i.e., the...