Thursday, 13:15 - 13:40 h, Room: H 0107


Coralia Cartis
On the evaluation complexity of constrained nonlinear programming

Coauthors: Nicholas I.m. Gould, Philippe L. Toint


We present a short-step target-following algorithm for smooth and nonconvexly constrained
programming problems that relies upon approximate first-order minimization of a nonsmooth
composite merit function and that takes at most O-2) problem-evaluations to generate an approximate KKT point or an infeasible point of the feasibility measure. This bound has the same order as that for steepest-descent methods applied to unconstrained problems. Furthermore, complexity bounds of (optimal) order ε-3/2 are obtained if cubic regularization steps for a smooth least-squares merit function are employed in a similar target-following algorithmic framework, provided higher accuracy is required for primal than for dual feasibility.


Talk 1 of the invited session Thu.2.H 0107
"Algorithms and applications I" [...]
Cluster 16
"Nonlinear programming" [...]


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