Shifted Variable Metric Methods for Unconstrained Optimization

A family of shifted variable metric methods for unconstrained optimization is investigated. These methods form a basis for shifted limited-memory variable metric methods introduced in second contribution in proceedings of SANM 2003. We describe basic properties of these methods, establish their global convergence and give conditions for the superlinear rate of convergence. Their efficiency is demonstrated by using extensive numerical experiments