Tuesday, May 11
MS22
Large-Scale Constrained Optimization
3:30 PM-5:30 PM
Room: Capitol South
Important advances have been made in the last few years in the design
and implementation of algorithms for large- scale constrained
optimization. Two competing approaches have emerged: active set and
interior methods. The speakers in this minisymposium will present
research in these two areas, and focus on important implementation
issues such as the reliable use of iterative methods for the solution
of the subproblems generated by the new methods.
Organizer: Jorge Nocedal
Northwestern University
- 3:30-3:55 On the Global Convergence of an SLP-Filter Algorithm
- Roger Fletcher, University of Dundee, Scotland
- 4:00-4:25 The Design of an Interior-Point Method for Nonlinear Programming
- Richard H. Byrd, University of Colorado, Boulder
- 4:30-4:55 The Use of Optimization (and Automatic
Differentiation) in Option Pricing and Hedging
- Thomas F. Coleman, Cornell University
- 5:00-5:25 An Assessment of Interior Methods for Nonlinear Programming
- Jean-Pierre
Goux, Northwestern University; Jorge Nocedal,
Organizer; and Guanghui Li, Northwestern University
MMD, 4/1/99