Title of Paper:A SCALED CONJUGATE GRADIENT METHOD WITH MOVING ASYMPTOTES FOR UNCONSTRAINED OPTIMIZATION PROBLEMS

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Affiliation of Author(s):理学院

Journal:JOURNAL OF INDUSTRIAL AND MANAGEMENT OPTIMIZATION

Key Words:Scaling conjugate gradient moving asymptotes the Wolfe condition unconstrained optimization

Abstract:In this paper, a scaled method that combines the conjugate gradient with moving asymptotes is presented for solving the large-scaled nonlinear unconstrained optimization problem. A diagonal matrix is obtained by the moving asymptote technique, and a scaled gradient is determined by multiplying the gradient with the diagonal matrix. The search direction is either a scaled conjugate gradient direction or a negative scaled gradient direction under different conditions. This direction is sufficient descent if the step size satisfies the strong Wolfe condition. A global convergence analysis of this method is also provided. The numerical results show that the scaled method is efficient for solving some large-scaled nonlinear problems.

ISSN No.:1547-5816

Translation or Not:no

Date of Publication:2017-04-01

Co-author:Zhou, Guanghui,Zeng, Meilan

Correspondence Author:nq