AI, Optimization and Machine Learning in OM Applications

Information Systems and Operations Management 

Intervenante: Georgia Perakis (MIT Sloan)

Salle Bernard Ramanantsoa

Abstract:

Data-driven decision-making has garnered a growing interest due to the increase in data availability in recent years. With that growth many opportunities as well as challenges arise. AI, Optimization and Machine Learning (ML) and their synergies can play an important role to address these challenges.  In fact, nowadays, predictive and prescriptive tasks arise together in Operations Management applications. This makes AI even more important. In this talk, we will discuss how AI connects with optimization and ML in some of these key applications. We will highlight the importance and challenges of integrating predictive and prescriptive tasks in data-driven decision-making. If time permits, we will also discuss the M&SOM journal and describe some of the new initiatives from this past year and the vision moving forward.