The search session has expired. Please query the service again.
The search session has expired. Please query the service again.
The search session has expired. Please query the service again.
The search session has expired. Please query the service again.
The search session has expired. Please query the service again.
The search session has expired. Please query the service again.
The search session has expired. Please query the service again.
The search session has expired. Please query the service again.
The search session has expired. Please query the service again.
The search session has expired. Please query the service again.
In this paper, we examine the influence of approximate first and/or
second derivatives on the filter-trust-region algorithm designed for
solving unconstrained nonlinear optimization problems and proposed by
Gould, Sainvitu and Toint in
[12]. Numerical
experiments carried out on small-scaled unconstrained problems from
the collection describe the effect of the use of
approximate derivatives on the robustness and the efficiency of the
filter-trust-region method.
Download Results (CSV)