5 citations · 7 across the 5 of their papers we have counts for
8 papers
The Value of Experiments in Assortment Optimization
Mohammadreza Ahmadnejadsaein, Amine Bennouna, Omar El Housni
Retailers can learn customer preferences by experimenting with different assortments. However, the cost of each experiment and the operational burden of repeatedly changing product…
AI-Mediation in Retail Markets: Revenue Effects and Assortment Optimization
Omar El Housni, Marouane Ibn Brahim
AI shopping assistants increasingly influence which products consumers consider. We study retail assortment planning under AI mediation, where a retailer chooses a catalog, an AI i…
Two-sided Assortment Optimization: Adaptivity Gaps and Approximation Algorithms
Omar El Housni, Ulysse Hennebelle, Alfredo Torrico
To address efficiency and design challenges in choice-based matching platforms, we introduce a two-sided assortment optimization framework under general choice preferences. The goa…
When Location Shapes Choice: Placement Optimization of Substitutable Products
Omar El Housni, Rajan Udwani
Strategic product placement can have a strong influence on customer purchase behavior in physical stores as well as online platforms. Motivated by this, we consider the problem of…
Maximum Load Assortment Optimization: Approximation Algorithms and Adaptivity Gaps
Omar El Housni, Marouane Ibn Brahim, Danny Segev
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 ch…
LP-based Approximations for Disjoint Bilinear and Two-Stage Adjustable Robust Optimization
Omar El Housni, Ayoub Foussoul, Vineet Goyal
We consider the class of disjoint bilinear programs where and $\m…
Matching Drivers to Riders: A Two-stage Robust Approach
Omar El Housni, Vineet Goyal, Oussama Hanguir +1
Matching demand (riders) to supply (drivers) efficiently is a fundamental problem for ride-sharing platforms who need to match the riders (almost) as soon as the request arrives wi…
Beyond Worst-case: A Probabilistic Analysis of Affine Policies in Dynamic Optimization
Omar El Housni, Vineet Goyal
Affine policies (or control) are widely used as a solution approach in dynamic optimization where computing an optimal adjustable solution is usually intractable. While the worst c…