TRUST REGION WITH NONLINEAR CONJUGATE GRADIENT METHOD

Abstract

Descent direction methods and trust region methods are usually used to solve the unconstrained optimization problem (p) (P ) min x∈R n f (x) .In this work, we are interested in convergence results that use trust region methods which employ the conjugate gradient method Day-Yuan version as a subprogram for each iteration.Further, we penalize the quadratic problems with constraints and convert them into series of unconstrained problems.