Seminar Details:

LANS Informal Seminar
"Scalable Strategies for Large-scale Structured Nonlinear Optimization"

DATE: May 7, 2014

TIME: 15:00:00 - 16:00:00
SPEAKER: Nai-Yuan Chiang, Postdoctoral Appointee, MCS, Argonne National Laboratory
LOCATION: Building 240, Room 1404-1405, Argonne National Laboratory

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.


Please send questions or suggestions to Jeffrey Larson: jmlarson at anl dot gov.