Wednesday, May 22
10:00 AM-12:00 PM
Saanich 1

MS27
Beyond Taylor Series Approxi-mations: The Use of Alternative Models in Nonlinear Programming

It is standard practice in nonlinear programming to exploit firstorder and secondorder information about the objective function and the constraints. This information is typically used to construct the Taylor series approximations that are required by globalized quasiNewton methods. When it works, this strategy is extremely effective, as evidenced by the popularity of quasiNewton methods and the elegant convergence theory that supports them.

But what can be done when, as often occurs in practice, the standard techniques do not apply? What if the objective function is not differentiable, or reliable derivatives are not available? The speakers will examine several promising ideas for nonstandard modeling strategies that address these issues.

Organizer: Virginia Torczon,
College of William and Mary

Global Modeling for Optimization
Paul Frank, Boeing Information and Support Services
An Approach to Derivative-Free Optimization
Andrew R. Conn, IBM T.J. Watson Research Center
Managing Approximation Models in Optimization
J.E. Dennis, Jr., Rice University
Local Quadratic Models in Stochastic Optimization
Michael W. Trosset, University of Arizona

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MEM, 3/18/96