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LANS Informal Seminar: Nai-Yuan Chiang
May 7, 2014 @ 15:00 CDT
Seminar Title: Scalable Strategies for Large-scale Structured Nonlinear Optimization
Speaker: Nai-Yuan Chiang, Postdoctoral Appointee, MCS, Argonne National Laboratory
Date/Time: 2014-05-07 15:00
Location: Building 240, Room 1404-1405
Description:
A robust and efficient parallel nonlinear solver is alway a challenge for large-scale stochastic NLP problems. We discuss the details of our implementation PIPS-NLP, which is based a parallel nonlinear interior-point solver. The parallel strategy is designed by decomposing the problem structure and building the Schur Complement.
Our nonlinear interior-point algorithm adopts a filter-based line search method. In order to guarantee the global convergence of the filter algorithm, we apply a curvature test instead of the inertia test. We present the global convergence analysis and also some numerical results based on CUTEr test problems and real energy applications.