A global optimization method for the stackelberg problem with convex functions via problem transformation and concave programming

A global optimization method is proposed for solving the Stackelberg problem through problem transformation and concave programming. The proposed method is applicable to a broad class of the Stackelberg problem, in which each function in upper-level is convex or a difference of two convex functions, and that in lower-level is convex.