A new DL-type conjugate gradient method for nonconvex unconstrained optimization problems(in Chinese)

Release time:2016-04-22

Affiliation of Author(s):Central South University

Teaching and Research Group:department of information science

Journal:Mathematica Numerica Sinica

Place of Publication:Beijing

Funded by:National natural science foundation (Authorized No:71071162,70921001)

Key Words:unconstrained program; conjugate gradient; global convergence; inexact line search; descant

Abstract:In this paper, a new DL-type conjugate gradient method is proposed for solving nonconvex unconstrained optimization problems. Different from the existent ones, a new modified Armijo-type line search rule is constructed to give both the steplength and the conjugated parameter being used to determine a search direction in the mean time at each iteration. Under weak conditions, the global convergence of the developed algorithm is established. Numerical experiments show the efficiency of the algorithm, particularly in comparison with the similar

Co-author:邓松海, 万中

Indexed by:Unit Twenty Basic Research

Document Type:J

Volume:34

Issue:3

Page Number:297-308

ISSN No.:0254-7791

Translation or Not:no

Date of Publication:2012-08-14