Wednesday Morning, October 25

MS25 Interior-Point Methods for Large-Scale Nonlinear Programming Problems I (Part I of II)

Sponsored by SIAM Activity Group on Optimization

Nonlinear programming formulations arising in many applications such as optimal control, inverse problems, and parameter identification have many inequality constraints and a large number of variables. Interior-point methods have emerged as a strong candidate to solve these problems. The aim of this minisymposium is to review current interior-point algorithms, their implementations and applications. The main approaches are primal-dual methods, trust-region affine-scaling algorithms and barrier methods.

Organizers: John E. Dennis, Rice University; Matthias Heinkenschloss, Virginia Polytechnic Institute and State University; and Luis N. Vicente, Rice University
Chair: Matthias Heinkenschloss

8:00 An Interior and Trust Region Approach for Nonlinear Programming
Yuying Li and Thomas F. Coleman, Cornell University

8:30 Strategies for Treating Indefiniteness in a Primal-Dual Method for Nonlinear Programming
Margaret H. Wright and David M. Gay, AT&T Bell Laboratories, and Michael Overton, Courant Institute of Mathematical Sciences, New York University

9:00 Trust-Region Interior-Point SQP Algorithms with Applications to Optimal Control Problems
Luis N. Vicente, John E. Dennis, and Matthias Heinkenschloss, Organizers

9:30 A Superlinear Infeasible-Interior-Point Method for Convex Programming and Monotone Nonlinear Complementarity Problems
Stephen Wright, Argonne National Laboratory and Danny Ralph, University of Melbourne, Australia

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