We develop a distribution-free model to evaluate the performance of process flexibility structures when only the mean and partial expectation of the demand are known. We characterize the worst-case demand distribution under general concave objective functions, and applying it to derive tight...

We study a hybrid strategy that uses both process flexibility and finished goods inventory for supply chain risk mitigation. The interplay between process flexibility and inventory is modeled as a two-stage robust optimization problem. In the first stage, the firm allocates inventory before...

We propose a new approach for the vehicle routing problem with stochastic customer demands revealed before vehicles are dispatched. We combine ideas from vehicle routing and manufacturing process flexibility to propose overlapped routing strategies with customer sharing. We characterize the...

We study in this paper a revenue management problem with add-on discounts. The problem is motivated by the practice in the video game industry, where a retailer offers discounts on selected supportive products (e.g. video games) to customers who have also purchased the core products (e.g. video...

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...

Motivated by applications in inventory control and real-time bidding, we consider un-discounted reinforcement learning (RL) in Markov decision processes (MDPs) under temporal drifts. In this setting, both the reward and state transition distributions are allowed to evolve over time, as long as...

We consider an online assortment optimization problem where we have n substitutable products with fixed reusable capacities c1,...,cn. In each period t, a user with some preferences (potentially adversarially chosen) arrives to the seller's platform who offers a subset of products St, from the...

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...

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...

We study the classic multi-period joint pricing and inventory control problem in a data-driven setting.In this problem, a retailer makes periodic decisions on the prices and inventory levels of an item that she wishes to sell. The retailer's objective is to maximize the expected profit over a...