Diagonal quasi-Newton method via variational principle under generalized Frobenius norm. (1st November 2016)

• Record Type: Journal Article
• Authors: Enshaei, Sharareh; June Leong, Wah; Farid, Mahboubeh
• Is Part Of: Optimization methods and software. Volume 31:Number 6(2016)
• Page Start: 1258
• Page End: 1271
• Publication Date: 2016-11-01
• Subjects: diagonal quasi-Newton updates -- variational principle -- weak secant equation -- inverse Hessian approximation -- weighted Frobenius norm; 65K10 -- 90C06 -- 90C53; Mathematical optimization -- Periodicals; Algorithms -- Periodicals; 519.7
• DOI: 10.1080/10556788.2016.1196205
• Languages: English
• ISSNs: 1055-6788

Abstract

Abstract : In this work, we present a new class of diagonal quasi-Newton methods for solving large-scale unconstrained optimization problems. The methods are derived by means of variational principle under the generalized Frobenius norm. We show global convergence of our methods under the standard line search with Armijo condition. Numerical results are carried out in standard test problems and clearly indicate vast superiority over some classical conjugate gradient methods.