Dr. Matthew Galati, Distinguished Operations Research Specialist at SAS, will join us to learn how the inputs driven by predictive analytics are used in mathematical optimization to solve intersecting problems. Dr. Galati is an enthusiastic speaker and a great instructor; here is a short story about his work at SAS.
This session will be open to everyone in the StatSci department.
Introduction to Mathematical Optimization
Prescriptive analytics is the study of the trade-offs inherent in decision making. Mathematical Optimization (MO) is a formal methodology for making decisions that optimize some objective function subject to a set of constraints. Predictive analytics provide the inputs that are used to construct MO models. This talk provides a brief introduction to mathematical optimization and its solution methods. We will explore various applications of MO, including selecting the best table to seat your Crazy Uncle Louie at your wedding.
Matthew Galati works in the Scientific Computing Department at SAS as a Distinguished Operations Research Specialist. At SAS since 2004, he focuses mostly on product development in two areas: mixed integer linear programming (MILP) and graph theory/network flow algorithms. In addition, he spends some of his time consulting on difficult problems through the Analytics Center of Excellence group. Matthew has a B.S. in Mathematics from Stetson University and an M.S. and Ph.D. in Operations Research from Lehigh University.