It is widely believed that "a little flexibility added at the right place can reap significant benefits for operations". Unfortunately, despite the extensive literature on this topic, we are not aware of any general methodology that can be used to guide managers to design sparse (i.e., slightly...

In many countries, the COVID-19 vaccination program faces great challenges, from the management of limited and irregular supply of vaccines, uncertain vaccine take-up rate from the population, and appropriate appointment booking management to reduce congestion etc. In addition, the feature of a...

In this paper, we develop a data-driven approach to recover the “right” choice model for the multi-product pricing problem, using the theory of a representative consumer in discrete choice. This approach uses a regularization function to capture diversification in choice behaviour, and...

This paper studies how to schedule medical appointments with time-dependent patient no-show behavior and random service times. The problem is motivated by our studies of independent datasets from countries in two continents which unanimously identify a significant time-of-day effect on patient...

A mixture of multinomial logits (MMNL) generalizes the single logit model, which is commonly used in predicting the probabilities of different outcomes. While extensive algorithms have been developed in the literature to learn MMNL models, theoretical results are limited. Built on the Frank...