1 research outputs found
Efficient Parameter Selection for Scaled Trust-Region Newton Algorithm in Solving Bound-constrained Nonlinear Systems
We investigate the problem of parameter selection for the scaled trust-region
Newton (STRN) algorithm in solving bound-constrained nonlinear equations.
Numerical experiments were performed on a large number of test problems to find
the best value range of parameters that give the least algorithm iterations and
function evaluations. Our experiments demonstrate that, in general, there is no
best parameter to be chosen and each specific value shows an efficient
performance on some problems and weak performance on other ones. In this
research, we report the performance of STRN for various choices of parameters
and then suggest the most effective one