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
7/27/95