Asmundis, Roberta De; Serafino, Daniela di; Hager, William - In: Computational Optimization and Applications 59 (2014) 3, pp. 541-563
We propose a new gradient method for quadratic programming, named SDC, which alternates some steepest descent (SD) iterates with some gradient iterates that use a constant steplength computed through the Yuan formula. The SDC method exploits the asymptotic spectral behaviour of the Yuan...