A conjugate gradient method for solving large-scale nonsmooth minimizations
LI Yong1， LI Zhiqun2
1.School of Mathematics and Statistics， Baise University， Baise， Guangxi 533000， China；2.School of Science， Beibu Gulf University， Qinzhou， Guangxi 535011， China
Abstract：For large-scale nonsmooth minimizations， this paper designs a modified LS conjugate gradient algorithm by Moreau-Yosida regular technique and the Armijo-type line search. The search direction of the proposed algorithm not only possesses the sufficient descent property but also belongs to a trust region. The global convergence is established under suitable conditions. Preliminary numerical results display that the new algorithm is better than those of the LMBM method and MPRP method for solving large-scale nonsmooth unconstrained convex optimization problems.
2019, Vol. 53 
