Network Revenue Management (NRM) describes a general online allocation problem in which combinations of capacity-constrained resources are sold to a stream of arriving customers. Existing papers propose one-size-fits-all approaches for controlling the capacities of these different resources over...

Motivated by the dynamic assortment offerings and item pricings occurring in e-commerce, we study a general problem of allocating finite inventories to heterogeneous customers arriving sequentially. We analyze this problem under the framework of competitive analysis, where the sequence of...

In this paper, we consider a personalized assortment planning problem under inventory constraints, where the type of each arriving customer is defined by a primary item of interest. As long as that item is in stock, the customer adds it to her shopping cart, at which point the retailer can...

This work is motivated by our collaboration with a large consumer packaged goods (CPG) company. We have found that while the company appreciates the advantages of dynamic pricing, they deem it operationally much easier to plan out a static price calendar in advance.We investigate the efficacy of...

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 consider an assortment optimization problem where a customer chooses a single item from a sequence of sets shown to her, while limited inventories constrain the items offered to customers over time. In the special case where all of the assortments have size one, our problem captures the...

We study an online knapsack problem where the items arrive sequentially and must be either immediately packed into the knapsack or irrevocably discarded. Each item has a different size and the objective is to maximize the total size of items packed. We focus on the class of randomized algorithms...

Firms typically require multiple sales observations under varying prices to understand how the demand for their items respond to price. In this paper, our partner online retailer is faced with the problem of reconstructing demand curves when only a single point on each curve has been...

It has long been known in the economics literature that selling different goods in a single bundle can significantly increase revenue, even when the valuations for the goods are independent. However, bundling is no longer profitable if the goods have high production costs. To overcome this...

In this work, we study data-driven decision-making and depart from the classical identically and independently distributed (i.i.d.) assumption. We present a new framework in which historical samples are generated from unknown and different distributions, which we dub heterogeneous environments....