@article{1009.90112,
author="Hinterm\"uller, M.",
title="{Solving nonlinear programming problems with noisy function values and
noisy gradients.}",
language="English",
journal="J. Optimization Theory Appl. ",
volume="114",
number="1",
pages="133-169",
year="2002",
doi={10.1023/A:1015416221909},
abstract="{Author's summary: An efficient algorithm for solving nonlinear
programs with noisy equality constraints is introduced and analyzed. The
unknown exact constraints are replaced by surrogates based on the bundle
idea, a well-known strategy from nonsmooth optimization. This concept allows
us to perform a fast computation of the surrogates by solving simple
quadratic optimization problems, control the memory needed by the algorithm,
and prove the differentiability properties of the surrogate functions. The
latter aspect allows us to invoke a sequential quadratic programming method.
The overall algorithm is of the quasi-Newton type. Besides convergence
theorems, qualification results are given and numerical test runs are
discussed.}",
reviewer="{Klaus Schittkowski (Bayreuth)}",
keywords="{noisy functions; nonlinear programming; quasi-Newton methods;
sequential quadratic programming}",
classmath="{*90C30 (Nonlinear programming)
90C55 (Methods of successive quadratic programming type)
90C31 (Sensitivity, etc.)
}",
}