TY - JOUR
T1 - A Nonmonotonic Trust Region Technique for Nonlinear Constrained Optimization
AU - Zhu , De-Tong
JO - Journal of Computational Mathematics
VL - 1
SP - 20
EP - 31
PY - 1995
DA - 1995/02
SN - 13
DO - http://doi.org/
UR - https://global-sci.org/intro/article_detail/jcm/9248.html
KW - 
AB - <p style="text-align: justify;">In this paper, a nonmonotonic trust region method for optimization problems with equality constraints is proposed by introducing a nonsmooth merit function and adopting a correction step. It is proved that all accumulation points of the iterates generated by the proposed algorithm are Kuhn-Tucker points and that the algorithm is $q$-superlinearly convergent.</p>