Thomas Magnanti

Thomas Magnanti is an Institute Professor and a Professor of Operations Research at the MIT Sloan School of Management. His research focuses on Operations Research and Statistics, with an emphasis on the theory and application of large-scale optimization systems. These include communications systems, production planning and scheduling, transportation planning, facility location, logistics, and network design. Magnanti is the co-author of two textbooks, Applied Mathematical Programming and Network Flows: Theory, Algorithms, and Applications. He holds a BS in chemical engineering from Syracuse University as well as an MS in statistics, an MS in mathematics, and a PhD in operations research from Stanford University.

Thomas Magnanti is an expert in Operations Research, with a focus on network flows, network design, and transportation planning. His research explores models and algorithms for solving complex optimization problems, including vehicle routing, network routing, and capacitated network design. He has contributed to the development of Benders decomposition techniques and dual-ascent procedures for large-scale problems. His work also addresses nonconvex piecewise linear cost minimization, two-facility capacitated network loading, and the convex hull of network design problems. Magnanti's publications emphasize the application of mathematical programming to real-world challenges in transportation and logistics.