A Conjugate Gradient Algorithm under Yuan-Wei-Lu Line Search Technique for Large-Scale Minimization Optimization Models. (15th January 2018)

• Record Type: Journal Article
• Authors: Li, Xiangrong; Wang, Songhua; Jin, Zhongzhou; Pham, Hongtruong
• Other Names: Cabrera-Guerrero Guillermo Academic Editor.
• Is Part Of: Mathematical problems in engineering. Volume 2018(2018)
• Publication Date: 2018-01-15
• Subjects: Engineering mathematics -- Periodicals; 510.2462
• DOI: 10.1155/2018/4729318
• Languages: English
• ISSNs: 1024-123X

Abstract

Abstract : This paper gives a modified Hestenes and Stiefel (HS) conjugate gradient algorithm under the Yuan-Wei-Lu inexact line search technique for large-scale unconstrained optimization problems, where the proposed algorithm has the following properties:( 1 ) the new search direction possesses not only a sufficient descent property but also a trust region feature;( 2 ) the presented algorithm has global convergence for nonconvex functions;( 3 ) the numerical experiment showed that the new algorithm is more effective than similar algorithms.