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We study the assortment optimization problem under the Sequential Multinomial Logit (SML), a discrete choice model that generalizes the multinomial logit (MNL). Under the SML model, products are partitioned into two levels, to capture…

Discrete Mathematics · Computer Science 2018-08-31 Alvaro Flores , Gerardo Berbeglia , Pascal van Hentenryck

An opaque product is a product for which only partial information is disclosed to the buyer at the time of purchase. Opaque products are common in sectors such as travel and online retail, where the car type or product color is hidden in…

Optimization and Control · Mathematics 2025-02-13 Omar El Housni , Adam N. Elmachtoub , Harsh Sheth , Jiaqi Shi

We consider an assortment optimization problem under the multinomial logit choice model with general covering constraints. In this problem, the seller offers an assortment that should contain a minimum number of products from multiple…

Optimization and Control · Mathematics 2025-10-06 Omar El Housni , Qing Feng , Huseyin Topaloglu

Motivated by e-commerce, we study the online assortment optimization problem. The seller offers an assortment, i.e. a subset of products, to each arriving customer, who then purchases one or no product from her offered assortment. A…

Machine Learning · Computer Science 2017-04-04 Wang Chi Cheung , David Simchi-Levi

We study assortment and price optimization under the generalized nested logit (GNL) model, one of the most general and flexible modeling frameworks in discrete choice modeling. Despite its modeling advantages, optimization under GNL is…

General Economics · Economics 2026-01-09 Hoang Giang Pham , Tien Mai

We study the dynamic assortment planning problem, where for each arriving customer, the seller offers an assortment of substitutable products and customer makes the purchase among offered products according to an uncapacitated multinomial…

Machine Learning · Statistics 2019-02-11 Xi Chen , Yining Wang , Yuan Zhou

We study an assortment optimization problem under a multi-purchase choice model in which customers choose a bundle of up to one product from each of two product categories. Different bundles have different utilities and the bundle price is…

Data Structures and Algorithms · Computer Science 2022-10-12 Xin Chen , Jiachun Li , Menglong Li , Tiancheng Zhao , Yuan Zhou

We consider the dynamic assortment optimization problem under the multinomial logit model (MNL) with unknown utility parameters. The main question investigated in this paper is model mis-specification under the $\varepsilon$-contamination…

Machine Learning · Statistics 2022-07-12 Xi Chen , Akshay Krishnamurthy , Yining Wang

We study the problem of optimizing assortment decisions in the presence of product-specific costs when customers choose according to a multinomial logit model. This problem is NP-hard and approximate solutions methods have been proposed in…

Optimization and Control · Mathematics 2023-12-05 Markus Leitner , Andrea Lodi , Roberto Roberti , Claudio Sole

Assortment optimization is a critical tool for online retailers aiming to maximize revenue. However, optimizing purely for revenue can lead to unbalanced sales across products, potentially causing a long tail of low-selling products and…

Computer Science and Game Theory · Computer Science 2026-03-16 Omar El Housni , Qing Feng , Huseyin Topaloglu

Optimizing the assortment of products to display to customers is a key to increasing revenue for both offline and online retailers. To trade-off between exploring customers' preference and exploiting customers' choices learned from data, in…

Machine Learning · Computer Science 2022-04-25 Hongbin Zhang , Yu Yang , Feng Wu , Qixin Zhang

We consider the problem of static assortment optimization, where the goal is to find the assortment of size at most $C$ that maximizes revenues. This is a fundamental decision problem in the area of Operations Management. It has been shown…

Methodology · Statistics 2011-08-19 Vivek Farias , Srikanth Jagabathula , Devavrat Shah

Assortment optimization has received active explorations in the past few decades due to its practical importance. Despite the extensive literature dealing with optimization algorithms and latent score estimation, uncertainty quantification…

Machine Learning · Statistics 2023-05-05 Shuting Shen , Xi Chen , Ethan X. Fang , Junwei Lu

In this paper, we study the assortment optimization problem faced by many online retailers such as Amazon. We develop a \emph{cascade multinomial logit model}, based on the classic multinomial logit model, to capture the consumers'…

Machine Learning · Computer Science 2020-07-15 Shaojie Tang , Jing Yuan

We study a stylized dynamic assortment planning problem during a selling season of finite length $T$. At each time period, the seller offers an arriving customer an assortment of substitutable products and the customer makes the purchase…

Machine Learning · Statistics 2021-02-22 Xi Chen , Chao Shi , Yining Wang , Yuan Zhou

Price differentiation is a common strategy in many markets. In this paper, we study a static multiproduct price optimization problem with demand given by a discrete mixed multinomial logit model. By considering a mixed logit model that…

Optimization and Control · Mathematics 2023-04-05 Ahmadreza Marandi , Virginie Lurkin

We study the assortment optimization problem under general linear constraints, where the customer choice behavior is captured by the Cross-Nested Logit model. In this problem, there is a set of products organized into multiple subsets (or…

Optimization and Control · Mathematics 2023-04-19 Cuong Le , Tien Mai

Selecting which products to display and at what prices is a central decision in retail and e-commerce operations. In many applications, these two choices must be made jointly under limited display capacity and uncertain customer demand. In…

Optimization and Control · Mathematics 2026-04-22 Yunfan Zhang , Yuxuan Han , Hongyu Shan , Jose Blanchet , Zhengyuan Zhou

Scalable real-time assortment optimization has become essential in e-commerce operations due to the need for personalization and the availability of a large variety of items. While this can be done when there are simplistic assortment…

Artificial Intelligence · Computer Science 2021-03-03 Theja Tulabandhula , Deeksha Sinha , Saketh Karra

We study an online joint assortment-inventory optimization problem, in which we assume that the choice behavior of each customer follows the Multinomial Logit (MNL) choice model, and the attraction parameters are unknown a priori. The…

Machine Learning · Computer Science 2025-01-03 Yong Liang , Xiaojie Mao , Shiyuan Wang
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