Hybrid methods in nonlinear programming

To construct robust and efficient optimization methods it is advantageous to combine a globally convergent algorithm and a locally superlinearly convergent one. Many of the proposed hybrid methods can be regarded as realizations of a general principle. For this class of methods (examples included) a general convergence result is presented.