### Optimization and Systems Theory Seminar

Friday, September 8, 2006, 11.00-12.00, Room 3721, Lindstedtsvägen 25

** Josh Griffin **

Sandia National Labs

Livermore, California

E-mail: jgriffi@sandia.gov

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A parallel, asynchronous method for derivative-free nonlinear programs

A strong need for derivative-free algorithms exists in the context of real-world optimization problems
where function evaluations can be computationally expensive and noisy. The objective and constraint functions
commonly exist as simple script interfaces to CPU intensive model analysis software. A single evaluation may
involve invoking cumbersome simulation codes whose run time is measured in hours. In this context, we present
an asynchronous parallel implementation of a derivative-free augmented Lagrangian algorithm for handling general
nonlinear constraints. The method requires approximate minimizers to a series of linearly constrained subproblems
involving the augmented Lagrangian of the nonlinear constraints. These subproblem are solved using a generating
set search algorithm capable of handling degenerate linear constraints. The objective and nonlinear constraint
functions are computed asynchronously in parallel.

A description and theoretical analysis of the algorithm will be given followed by numerical results.

Calendar of seminars

*Last update: August 16, 2006 by
Marie Lundin.
*