期刊
AIMS MATHEMATICS
卷 6, 期 10, 页码 10742-10764出版社
AMER INST MATHEMATICAL SCIENCES-AIMS
DOI: 10.3934/math.2021624
关键词
conjugate gradient method; inexact line search; global convergence
资金
- University of Malaysia Terengganu (UMT)
The paper introduces a new conjugate gradient method for solving unconstrained optimization problems, which shows better efficiency compared to other existing methods.
The conjugate gradient (CG) method is a method to solve unconstrained optimization problems. Moreover CG method can be applied in medical science, industry, neural network, and many others. In this paper a new three term CG method is proposed. The new CG formula is constructed based on DL and WYL CG formulas to be non-negative and inherits the properties of HS formula. The new modification satisfies the convergence properties and the sufficient descent property. The numerical results show that the new modification is more efficient than DL, WYL, and CG-Descent formulas. We use more than 200 functions from CUTEst library to compare the results between these methods in term of number of iterations, function evaluations, gradient evaluations, and CPU time.
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