@Article{JCM-13-1,
author = {Zhu, De-Tong},
title = {A Nonmonotonic Trust Region Technique for Nonlinear Constrained Optimization},
journal = {Journal of Computational Mathematics},
year = {1995},
volume = {13},
number = {1},
pages = {20--31},
abstract = {<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>},
issn = {1991-7139},
doi = {https://doi.org/1995-JCM-9248},
url = {https://global-sci.com/article/85804/a-nonmonotonic-trust-region-technique-for-nonlinear-constrained-optimization}
}