T. Plantenga, A TRUST REGION METHOD FOR NONLINEAR-PROGRAMMING BASED ON PRIMAL INTERIOR-POINT TECHNIQUES, SIAM journal on scientific computing (Print), 20(1), 1999, pp. 282-305
This paper describes a new trust region method for solving large-scale
optimization problems with nonlinear equality and inequality constrai
nts. The new algorithm employs interior-point techniques from linear p
rogramming, adapting them for more general nonlinear problems. A softw
are implementation based entirely on sparse matrix methods is describe
d. The software handles infeasible start points, identifies the active
set of constraints at a solution, and can use second derivative infor
mation to solve problems. Numerical results are reported for large and
small problems, and a comparison is made with other large-scale optim
ization codes.