Koç University Industrial Engineering Graduates Win INFORMS Prize Honorable Mention The Institute for Operations Research and the Management Sciences (INFORMS) is the largest professional society in the world for individuals in the field of operations research, management science and analytics. INFORMS Undergraduate Operations Research Prize is held annually to recognize a student or group of students who have conducted a significant applied project in operations research or management science and/or original, important theoretical or applied research in operations research or management science while enrolled as an undergraduate. This year the competition had contestants from Massachusets Institute of Technology (MIT), India Institute of Technology (IIT), Koç University, North Carolina State University, Bilkent University and University of Michigan. The project group, Cem Aydin, Alp Aribal, Atiye Cansu Erol and Begum Tuglu, completed their graduation project titled “A Reformulation of the Appointment Scheduling Problem with Customer Choice Behavior and Multiple Customer Types” under the supervision of Prof. Lerzan Ormeci in Spring 2016. They initially worked in collaboration with Yapı Kredi Teknoloji, and later transformed the work into a theoretical paper on revenue management. This project has won Honorable Mention in INFORMS Undergraduate Operations Research Prize. This award is given to the second-best project participating in the competition. Cem Aydin presented their work in 2016 INFORMS Annual Meeting in Nashville, TN in the US. The Honorable Mention Prize was prize was shared with Hari Bandi from India Institute of Technology. The winner of the contest was Joy Chang from University of Michigan with her work “Carsharing Fleet Location Design with Mixed Vehicle Types for CO2 Emission Reduction”. The project reformulated the intractably large appointment scheduling problem involving customer choice as a problem of minimizing of the sum of opportunity costs of appointment offers, where these opportunity costs were calculated using consecutive value functions of the corresponding dynamic program. Their work establishes an easy to calculate upper bound for the general problem and opens up new modelling approaches for appointment scheduling, assortment optimization and network revenue management problems involving customer choice.