PDF下载 分享
[1]罗文军,吴泽忠,贺盛瑜.一类改进的拟牛顿算法[J].成都信息工程大学学报,2024,39(03):374-381.[doi:10.16836/j.cnki.jcuit.2024.03.016]
 LUO Wenjun,WU Zezhong,HE Shengyu.An Improved Quasi-Newtonian Algorithm[J].Journal of Chengdu University of Information Technology,2024,39(03):374-381.[doi:10.16836/j.cnki.jcuit.2024.03.016]
点击复制

一类改进的拟牛顿算法

参考文献/References:

[1] 王宜举,修乃华.非线性最优化理论与方法[M].北京:科学出版社,2016.
[2] Wei Z,Li G,Qi L.New quasi-Newton methods for unconstrained optimization problems[J].Applied Mathematics and Computation,2006,175(2):1156-1188.
[3] Andrei N.An unconstrained optimization test functions collection[J].Adv.Model.Optim,2008,10(1):147-161.
[4] Kochenderfer M J,Wheeler T A.Algorithms for optimization[M].Mit Press,2019.
[5] Armijo L.Minimization of functions having Lipschitz continuous first partial derivatives[J].Pacific Journal of mathematics,1966,16(1):1-3.
[6] Jorge N,Stephen J W.Numerical optimization[M].New York,NY:Spring New York,1999.
[7] Wei Z,Qi L,Chen X.An SQP-type method and its application in stochastic programs[J].Journal of Optimization Theory and Applications,2003,116(1):205-228.
[8] 袁亚湘,孙文瑜.最优化理论与方法[M].北京:科学出版社,1997.
[9] Dolan E D,Moré J J.Benchmarking optimization software with performance profiles[J].Mathematical programming,2002,91(2):201-213.
[10] Wu Q,Wei Z.Some new step-size rules for optimization problems[J].Journal of Shanghai University(English Edition),2007,11(2):135-141.

备注/Memo

收稿日期:2022-11-29
基金项目:国家自然科学基金资助项目(71962030); 四川省社科重点研究基地资助项目(Xq21B06); 国家社会科学基金资助项目(21BTQ099)

更新日期/Last Update: 2024-06-30