This work is a survey on the methods for large scale unconstrained optimization. Besides its own theoretical importance, the growing interest in the last years in solving problems with a larger and larger number of variables are arising very frequently from real world as a result of modeling systems with a very complex structure. In this paper the main methods for solving large scale unconstrained optimization problems are briefly described and an accurate choice of references is reported.