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A globally convergent hybrid conjugate gradient method with strong Wolfe conditions for unconstrained optimization

A globally convergent hybrid conjugate gradient method with strong Wolfe conditions for unconstrained optimization

Abstract In this paper, we develop a new hybrid conjugate gradient method that inherits the features of the Liu and Storey (LS), Hestenes and Stiefel (HS), Dai and Yuan (DY) and Conjugate Descent (CD) conjugate gradient methods. The new method generates a descent direction independently of any line search and …