Tuesday, 13:15 - 13:40 h, Room: H 0110

 

Denis Ridzal
A matrix-free trust-region SQP algorithm for large-scale optimization

Coauthors: Miguel Aguilo, Joseph Young

 

Abstract:
We present an inexact trust-region sequential quadratic
programming (SQP) method for the matrix-free solution of
large-scale nonlinear programming problems. First, we
discuss recent algorithmic advances in the handling of
inequality constraints. Second, for optimization problems
governed by partial differential equations (PDEs) we
introduce a class of preconditioners for optimality
systems that are easily integrated into our matrix-free
trust-region framework and that efficiently reuse the
available PDE solvers. We conclude the presentation with
numerical examples in acoustic design, material inversion
in elastodynamics and optimization-based failure analysis.

 

Talk 1 of the invited session Tue.2.H 0110
"Nonlinear optimization V" [...]
Cluster 16
"Nonlinear programming" [...]

 

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