We study the space constrained assortment optimization problem under the paired combinatorial logit choice model. The goal in this problem is to choose a set of products to make available for purchase with the intention of maximizing the expected revenue from each arriving customer. Each offered...

In this paper, we introduce the Multi-Purchase Multinomial Logit choice model, which extends the random utility maximization framework of the classical Multinomial Logit model to a multiple-purchase setting. In this model, customers sample random utilities for each offered product as in the...

We introduce the click-based MNL choice model, a novel framework for capturing customer purchasing decisions in e-commerce settings. We augment the classical Multinomial Logit choice model with the assumption that customers only consider the items they have clicked on before they proceed to...

In this paper, we consider an assortment optimization problem in which a platform mustchoose pairwise disjoint sets of assortments to offer across a series of T stages. Arrivingcustomers begin their search process in the first stage and progress sequentially throughthe stages until their...

We study assortment optimization problems under a natural variant of the multinomial logit model where the customers are willing to focus only on a certain number of products that provide the largest utilities. In particular, each customer has a rank cutoff, characterizing the number of products...