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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

In contextual dynamic pricing, a seller sequentially prices goods based on contextual information. Buyers will purchase products only if the prices are below their valuations. The goal of the seller is to design a pricing strategy that…

Machine Learning · Statistics 2025-02-14 Matilde Tullii , Solenne Gaucher , Nadav Merlis , Vianney Perchet

We study contextual dynamic pricing problems where a firm sells products to $T$ sequentially-arriving consumers, behaving according to an unknown demand model. The firm aims to minimize its regret over a clairvoyant that knows the model in…

Machine Learning · Computer Science 2025-04-07 Zifeng Zhao , Feiyu Jiang , Yi Yu

Motivated by modern-day applications such as Attended Home Delivery and Preference-based Group Scheduling, where decision makers wish to steer a large number of customers toward choosing the exact same alternative, we introduce a novel…

Optimization and Control · Mathematics 2025-02-13 Omar El Housni , Marouane Ibn Brahim , Danny Segev

We consider the problem of multi-product dynamic pricing, in a contextual setting, for a seller of differentiated products. In this environment, the customers arrive over time and products are described by high-dimensional feature vectors.…

Machine Learning · Statistics 2020-05-19 Adel Javanmard , Hamid Nazerzadeh , Simeng Shao

Learning the optimal ordering of content is an important challenge in website design. The learning to rank (LTR) framework models this problem as a sequential problem of selecting lists of content and observing where users decide to click.…

Machine Learning · Computer Science 2023-05-12 James A. Grant , David S. Leslie

Assortment optimization concerns the problem of selling items with fixed prices to a buyer who will purchase at most one. Typically, retailers select a subset of items, corresponding to an "assortment" of brands to carry, and make each…

Computer Science and Game Theory · Computer Science 2022-05-23 Will Ma

The recent rising popularity of ultra-fast delivery services on retail platforms fuels the increasing use of urban warehouses, whose proximity to customers makes fast deliveries viable. The space limit in urban warehouses poses a problem…

Optimization and Control · Mathematics 2019-05-06 Rong Jin , David Simchi-Levi , Li Wang , Xinshang Wang , Sen Yang

We study dynamic joint assortment and pricing where a seller updates decisions at regular accounting/operating intervals to maximize the cumulative per-period revenue over a horizon $T$. In many settings, assortment and prices affect not…

Machine Learning · Statistics 2026-02-20 Junhui Cai , Ran Chen , Qitao Huang , Linda Zhao , Wu Zhu

We consider dynamic pricing with covariates under a generalized linear demand model: a seller can dynamically adjust the price of a product over a horizon of $T$ time periods, and at each time period $t$, the demand of the product is…

Machine Learning · Computer Science 2023-11-14 Hanzhao Wang , Kalyan Talluri , Xiaocheng Li

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

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

Contextual pricing strategies are prevalent in online retailing, where the seller adjusts prices based on products' attributes and buyers' characteristics. Although such strategies can enhance seller's profits, they raise concerns about…

Computer Science and Game Theory · Computer Science 2026-03-17 Pangpang Liu , Will Wei Sun

The assortment planning problem is a central piece in the revenue management strategy of any company in the retail industry. In this paper, we study a robust assortment optimization problem for substitutable products under a sequential…

Optimization and Control · Mathematics 2020-09-01 Saharnaz Mehrani , Jorge A. Sefair

Personalized pricing, which involves tailoring prices based on individual characteristics, is commonly used by firms to implement a consumer-specific pricing policy. In this process, buyers can also strategically manipulate their feature…

Machine Learning · Statistics 2024-06-27 Pangpang Liu , Zhuoran Yang , Zhaoran Wang , Will Wei Sun

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

Lately, personalized marketing has become important for retail/e-retail firms due to significant rise in online shopping and market competition. Increase in online shopping and high market competition has led to an increase in promotional…

Machine Learning · Computer Science 2020-10-19 Ankur Verma

We revisit the problem of large-scale assortment optimization under the multinomial logit choice model without any assumptions on the structure of the feasible assortments. Scalable real-time assortment optimization has become essential in…

Optimization and Control · Mathematics 2018-05-02 Deeksha Sinha , Theja Tulabandhula

Contextual dynamic pricing aims to set personalized prices based on sequential interactions with customers. At each time period, a customer who is interested in purchasing a product comes to the platform. The customer's valuation for the…

Machine Learning · Statistics 2023-03-07 Yiyun Luo , Will Wei Sun , and Yufeng Liu

We study the pricing problem faced by a firm that sells a large number of products, described via a wide range of features, to customers that arrive over time. Customers independently make purchasing decisions according to a general choice…

Machine Learning · Statistics 2018-01-03 Adel Javanmard , Hamid Nazerzadeh