Volume 13, Issue 2
Non-Quasi-Newton Updates for Unconstrained Optimization

Ya-xiang Yuan & Richard H. Byrd

J. Comp. Math., 13 (1995), pp. 95-107

Published online: 1995-04

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  • Abstract

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.

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@Article{JCM-13-95, author = {}, title = {Non-Quasi-Newton Updates for Unconstrained Optimization}, journal = {Journal of Computational Mathematics}, year = {1995}, volume = {13}, number = {2}, pages = {95--107}, abstract = { 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. }, issn = {1991-7139}, doi = {https://doi.org/}, url = {http://global-sci.org/intro/article_detail/jcm/9253.html} }
TY - JOUR T1 - Non-Quasi-Newton Updates for Unconstrained Optimization 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 - 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.
Ya-xiang Yuan & Richard H. Byrd. (1970). Non-Quasi-Newton Updates for Unconstrained Optimization. Journal of Computational Mathematics. 13 (2). 95-107. doi:
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