Hugo is enrolled in the Masters program and works in a project collaboration with the retail industry. Retailers usually face the problem of selecting assortments of products that are likely to generate high revenue by taking into account substitution among products. The objective of the project to predict the behavior of consumers on new products that have never been in store which have features in common with well-known products.
S. D. Jena, Andrea. A.Lodi, H. Palmer, 2017. Partially-Ranked Choice Models for Data-Driven Assortment Optimization. DS4DM-2017-011.
Hugo Palmer, 2016. Large-Scale Assortment Optimization. Cerc Data Science for Real-Time Decision-Making, Département de Mathématiques et de Génie Industriel, Polytechnique de Montréal. Décembre 2016