Saturday, September 23

Large-Scale Nonlinear Programming: Algorithms and Applications

10:30 AM-12:30 PM
Mt. Vernon

With the remarkable increase in computational capability, there has been a concomitant increase in the desire to apply optimization techniques to nonlinear mathematical models of phenomena arising from realistic engineering, science, and business applications. The problems under consideration in this session are characterized by having a large number of variables and/or constraints, thus the algorithms seek to exploit parallel and distributed platforms. Two speakers discuss gradient-based methods, in particular SQP methods, for solving PDE-based optimization problems. The third addresses optimization methods for problems where derivatives are unavailable, and the fourth deals with the the important problem of bounds constraints.

Organizer: Paul T. Boggs
Sandia National Laboratories, USA
10:30-10:55 Parallel Software for Large-Scale Optimization
Steven J. Benson, Lois Curfman McInnes, and Jorge Moré, Argonne National Laboratory, USA
11:00-11:25 A Class of Trust-Region Methods for Simulation-Based Optimization
Juan C. Meza and Patricia D. Hough, Sandia National Laboratories, USA
11:30-11:55 Parallel Algorithms for Large-Scale PDE-Constrained Optimization
Volkan Akcelik, George Biros, Ioannis Epanomeritakis, and Omar Ghattas, Carnegie Mellon University, USA
12:00-12:25 Tightly-coupled SQP Algorithms from Loosely-Coupled Components
Paul T. Boggs, Organizer

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