TY - JOUR
T1 - Non-Quasi-Newton Updates for Unconstrained Optimization
AU - Yuan , Ya-Xiang
AU - Byrd , Richard H.
JO - Journal of Computational Mathematics
VL - 2
SP - 95
EP - 107
PY - 1995
DA - 1995/04
SN - 13
DO - http://doi.org/
UR - https://global-sci.org/intro/article_detail/jcm/9253.html
KW - 
AB - <p style="text-align: justify;">In this report we present some new numerical methods for unconstrained optimization. These methods apply update formulae that do not satisfy the quasi-Newton equation. We derive these new formulae by considering different techniques of approximating the objective function. Theoretical analyses are given to show the advantages of using non-quasi-Newton updates. Under mild conditions we prove that our new update formulae preserve global convergence properties. Numerical results are also presented.</p>