A Nonmonotone Modified BFGS Algorithm for Nonconvex Unconstrained Optimization Problems

被引：0
|
作者：
Amini, Keyvan [1 ]
Bahrami, Somayeh [1 ]
Amiri, Shadi [1 ]
机构：
[1] Razi Univ, Fac Sci, Dept Math, Kermanshah, Iran
来源：
FILOMAT | 2016年 / 30卷 / 05期
关键词：
Unconstrained optimization; BFGS method; Quasi-Newton method; Nonmonotone line search; Global convergence; LINE SEARCH TECHNIQUE; QUASI-NEWTON METHODS; GLOBAL CONVERGENCE;
D O I：
10.2298/FIL1605283A
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
In this paper, a modified BFGS algorithm is proposed to solve unconstrained optimization problems. First, based on a modified secant condition, an update formula is recommended to approximate Hessian matrix. Then thanks to the remarkable nonmonotone line search properties, an appropriate nonmonotone idea is employed. Under some mild conditions, the global convergence properties of the algorithm are established without convexity assumption on the objective function. Preliminary numerical experiments are also reported which indicate the promising behavior of the new algorithm.
引用
收藏
页码：1283 / 1296
页数：14
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