ISyE Seminar Series: Prof. Andreas Wächter

"A Smoothing-Based Decomposition Framework for Nonlinear Two-Stage Optimization Problems"

Andreas Wächter

Professor in the Department of Industrial Engineering and Management Sciences
Northwestern University

About the Seminar:

We present a new decomposition framework for continuous nonlinear nonconvex two-stage optimization problems.  A barrier-based smoothing technique is used to render the second-stage recourse function differentiable, so that efficient standard nonlinear optimization methods and software can be utilized for the solution of both the master and subproblems.  We explore the convergence properties of the framework, which is particularly challenging because of the nonconvexity of the subproblems that could lead to local minima in addition to global optima.  We demonstrate the practical performance of the framework by solving large-scale optimal power flow problems where the network is decomposed into a transmission and several distribution systems.

About the Speaker:

Andreas Wächter is a Professor in the Department of Industrial Engineering and Management Sciences at Northwestern University.  His research interests include the design, analysis, implementation, and application of numerical algorithms for nonlinear continuous and mixed-integer optimization, scientific computing, power systems, and sustainability.  He obtained his master's degree in Mathematics at the University of Cologne, Germany, and his Ph.D. in Chemical Engineering at Carnegie Mellon University.  Before joining Northwestern University in 2011, he was a Research Staff Member in the Department of Mathematical Sciences at IBM Research in Yorktown Heights, NY.  He is a SIAM Fellow, and a recipient of the Wilkinson Prize for Numerical Software and the INFORMS Computing Society Prize for his work on the open-source optimization package Ipopt.