报告题目：Challenges in Solving Dynamic Optimization Problems

报告人：Prof. Lorenz T. Biegler
Bayer University Professor and Head Chemical Engineering Department,
Carnegie Mellon University, USA.

时间：2016年6月3日 周五 上午 9:30-11:00

地点:玉泉校区 工控新楼 105

报告摘要：
Dynamic optimization problems are widespread in chemical engineering. With the development of large-scale optimization tools, more challenging problems can now be considered. This talk focuses on three separate challenge areas related to dynamic optimization, as well as recent advances in tackling them. The first challenge deals with determination of accurate solutions to singular control problems. Such problems are ill-conditioned and often lead to nonunique profiles. To tackle this problem we present a bilevel approach where the basic problem is solved with fixed elements in the inner problem and moving finite elements and optimal regularization is solved in an outer problem. The next challenge deals large-scale dynamic formulations that need to accommodate uncertainty. We present and solve a multistage formulation as an efficient way to deal with the modeling features. Moreover, to deal with uncertainties we develop a back-off constraint formulation that handles uncertainties without increasing the cost for optimization. Finally, because increasing process model complexity places increasing demands on solving dynamic optimization problems, we consider a parallel approach for the solution of large-scale discretized optimization problems. In particular, we exploit the tridiagonal nature of the KKT system and demonstrate a novel decomposition based on Cyclic Reduction. Some preliminary scaling results demonstrate that this approach has tremendous potential to solve very large dynamic optimization problems very efficiently - and to meet the challenges of dealing with even more complex dynamic systems.

报告人简介：
Lorenz T. (Larry) Biegler is currently the Head and Bayer University Professor of Chemical Engineering at Carnegie Mellon University. His research interests lie in computer aided process engineering (CAPE) and include flowsheet optimization, optimization of systems of differential and algebraic equations, reactor network synthesis and algorithms for constrained, nonlinear process control. Contributions in these areas include analysis and development of nonlinear programming algorithms, optimization software design and application to real-world chemical processes and energy systems. He is an author on over 350 archival publications and 11 textbooks, has edited nine technical books and given numerous invited presentations at national and international conferences. His awards include the Lewis Award, Walker Award and Computers in Chemical Engineering Award, all given by AIChE, Curtis McGraw Research Award and CACHE Computing Award, given by ASEE, the INFORMS Computing Prize, and an honorary doctorate in engineering sciences from the Technical University of Berlin. He is a Fellow of AIChE and SIAM, and a member of the National Academy of Engineering.