Linear Optimization: The Interplay between Theory and Practice

A part of the Mechanical & Industrial Engineering Distinguished Seminar Series

Abstract

In the seventy years since G. B. Dantzig first developed the Simplex method for linear programming problems, it has become arguably the most useful and influential algorithm ever developed. The Simplex method, together with numerous variants and related algorithms that have been developed since then, are designed to solve a broad array of linear optimization problems covering a wide range of important real-world applications. However, for almost as long, researchers have struggled to understand the Simplex method’s phenomenal practical success in light of the theoretical inefficiency of the method, and to develop algorithms that are both theoretically and practically efficient for solving linear programs as well as more challenging integer and convex optimization problems. We will trace the spectacular progress of these methods, as well as the underlying theoretical challenges and developments. This talk requires no technical background in optimization.

Speaker biosketch

Ilan Adler is a Chancellor professor in the Operations Research and Industrial Engineering department at the University of California in Berkeley, which he joined in 1970. Professor Adler holds a B.A in Economics and Statistics from the Hebrew University in Israel (1966), a M.Sc. in Operations Research from the Technion in Israel (1967), and a Ph.D. in Operations Research from Stanford (1970). His main research interests are in the areas of Mathematical Programming, Game Theory, and Applied Probability.

Coffee and cookies will be served after the seminar.