Abstract We consider alternating minimization procedures for convex and non-convex optimization problems with the vector of variables divided into several blocks, each block being amenable respect to its while maintaining other blocks constant. In case two we prove a linear convergence rate an procedure under Polyak–Łojasiewicz (PL) condition, which can be seen as relaxation strong convexity as...

Abstract This article studies Gauss–Newton-type methods for over-determined systems to find solutions bilevel programming problems. To proceed, we use the lower-level value function reformulation of programs and consider necessary optimality conditions under appropriate assumptions. First, strict complementarity upper- feasibility constraints, prove convergence a method in computing points sati...