A new hybrid conjugate gradient algorithm for unconstrained optimization

Document Type: Research Paper

Authors

School of Mathematics and Statistics‎, ‎Southwest University‎, ‎Chongqing 400715‎, ‎P.R‎. ‎China.

Abstract

In this paper, a new hybrid conjugate gradient algorithm is proposed for solving unconstrained optimization problems. This new method can generate sufficient descent directions unrelated to any line search. Moreover, the global convergence of the proposed method is proved under the Wolfe line search. Numerical experiments are also presented to show the efficiency of the proposed algorithm, especially for solving highly dimensional problems.

Keywords

Main Subjects


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Volume 43, Issue 6
November and December 2017
Pages 2067-2084
  • Receive Date: 01 July 2016
  • Revise Date: 18 December 2016
  • Accept Date: 24 December 2016