Department of Industrial Engineering & Decision Analytics [IEDA Seminar]  - Choice Modeling and Assortment Optimization with Context Effects and Products from Two Categories 

10:30am - 12:00pm
Room 4582 (lift 27-28)

Discrete choice modeling and assortment optimization receive significant attentions in the revenue management community. Yet, the major focus has been on substitutable products from a single category in which a product’s perceived utility depends only on the product itself. In this talk, I will present two recent research projects to broaden the scope. In the first project, we introduce a new choice model, the "contextual multinomial logit" model, in which the utility of a presented item to the customer depends on what other items are offered beside it in an assortment. We show empirically that incorporating the context effects may significantly enhance the prediction scores compared with several widely used discrete choice models. In the second project, we analyze assortment optimization problems under the multivariate multinomial logit models and develop approximation algorithms with theoretical guarantees.

講者/ 表演者:
Prof. Xin CHEN
School of Industrial and Systems Engineering (ISyE), Georgia Institute of Technology

Xin Chen is the James C. Edenfield Chair and Professor in ISyE, Georgia Tech. He obtained his PhD in Operations Research from MIT (2003), MS in Computational Mathematics from Chinese Academy of Sciences (1998) and BS in Computational Mathematics from Xiangtan University (1995). His research interest lies in optimization, revenue management and supply chain management. He received the Informs revenue management and pricing section prize in 2009. He is the coauthor of the book "The Logic of Logistics: Theory, Algorithms, and Applications for Logistics and Supply Chain Management (Second Edition 2005 & Third Edition 2014)". His research interests are in data analytics; revenue management and dynamic pricing; operations research; operations management; optimization; optimal stochastic control; computational mathematics; and production, inventory and supply chain management.

Department of Industrial Engineering & Decision Analytics