Monday, 13:45 - 14:10 h, Room: H 0110


Sven Leyffer
Large-scale nonlinear optimization solvers


We describe the development of a suit of tools and solvers for large-scale nonlinearly constrained optimization problems. We emphasize methods that can operate in a matrix-free mode and avoid matrix factorizations. Our framework implements a range fo two-phase active-set methods, that are required, for example, for fast resolves in mixed-integer solvers. In the first phase, we estimate the active set, and in the second phase we perform a Newton step on the active constraints. We show that our framework can be designed in a matrix-free mode, and analyze its convergence properties. We show that allowing a small number of active-set changes in the Newton step improves convergence.


Talk 2 of the invited session Mon.2.H 0110
"Nonlinear optimization II" [...]
Cluster 16
"Nonlinear programming" [...]


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