Please use this identifier to cite or link to this item:
|Title:||Global convergence of nonmonotone descent methods for unconstrained optimization problems|
Nonmonotone line search
|Source:||Sun, W., Han, J., Sun, J. (2002). Global convergence of nonmonotone descent methods for unconstrained optimization problems. Journal of Computational and Applied Mathematics 146 (1) : 89-98. ScholarBank@NUS Repository. https://doi.org/10.1016/S0377-0427(02)00420-X|
|Abstract:||Global convergence results are established for unconstrained optimization algorithms that utilize a nonmonotone line search procedure. This procedure allows the user to specify a flexible forcing function and includes the nonmonotone Armijo rule, the nonmonotone Goldstein rule, and the nonmonotone Wolfe rule as special cases. © 2002 Elsevier Science B.V. All rights reserved.|
|Source Title:||Journal of Computational and Applied Mathematics|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Dec 14, 2017
WEB OF SCIENCETM
checked on Nov 20, 2017
checked on Dec 10, 2017
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.