| 本文已被：浏览次 下载次 |
码上扫一扫！ |
|
|
|
| A non-monotone super-memory gradient method based on trust region technique and modified quasi-Newton equation |
|
GONG En-long1, CHEN Shuang-shuang2, SUN Qing-ying2, CHEN Ying-mei2
|
|
(1.Qingdao Hotel Management College, Qingdao 266100, China;2.College of Science in China University of Petroleum, Qingdao 266580, China)
|
| Abstract: |
| Based on trust region technique and modified quasi-Newton equation, by combining with Neng-Zhu Gu non-monotone strategy, a new super-memory gradient method for unconstrained optimization problem was presented. The global and convergence properties of the new method were proved. It saves the storage and computation of some matrixes in its iteration, and is suitable for solving large scale optimization problems. The numerical results show that the new method is effective. |
| Key words: super-memory gradient method non-monotone step rule convergence convergence rate numerical experiment |
|
|