Tuesday, May 11

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
NewJean-Pierre Goux, Northwestern University; Jorge Nocedal, Organizer; and Guanghui Li, Northwestern University

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