but he did not specify what the nonlinearity actually means or what it actually infers. It is a bit hard to make a linear problem into nonlinear without a clear definition for it. So
I. Does the nonlinearity mean nonlinear objective function?
III. or does the NLO mean a problem with nonlinear constraints?
IV. or does the NLO mean a problem with nonlinear constraints and nonlinear objective function?
V. or instead of linear mapping is a NLO problem with an objective function with certain smoothness?
VI. and what kind of requirements a NLO problem require: what kind of convexity assumptions for domain and codomain? Does the function itself need to be convex or concave? More detailed question related to convex optimisation here.