Derivative Free Optimization Algorithm for Constrained Problems
Friday, April 16, 1999 - 10:10am - 11:00am
Vincent 570
Andrew Conn (IBM)
We consider a class of nonlinear optimization problems with expensive objective function and constraints. For such problems the derivatives of the objective function and, possibly, constraints are assumed unavailable. Also some noise may be present in the function computations. We will describe a class of, so called, derivative free optimization (DFO) algorithms developed for constrained and unconstrained problems.
This is joint work with Katya Scheinberg and Phillipe Toint.
This is joint work with Katya Scheinberg and Phillipe Toint.