We study a general problem of allocating limited resources to heterogeneous customers over time, under model uncertainty. Each type of customer can be serviced using different actions, each of which stochastically consumes some combination of resources, and returns different rewards for the...

We study the canonical quantity-based network revenue management (NRM) problem where the decision-maker must irrevocably accept or reject each arriving customer request with the goal of maximizing the total revenue given limited resources. The exact solution to the problem by dynamic programming...

The boom of e-commerce in the globe in recent years has expedited the expansion of fulfillment infrastructures by e-retailers. While e-retailers are building more warehouses to offer faster delivery service than ever, the associated fulfillment costs have skyrocketed over the past decade. In...

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....