A test problem generator for large-scale unconstrained optimization is described. It permits the generation of a poorly or well-conditioned problems of arbitrary size, derived from nonlinear network flow models. An eigenvalue analysis provides bounds on the condition number of the Hessian of the objective function and an example of an efficient preconditioner, using these bounds, is outlined.
['Ron S. Dembo', 'Trond Steihaug']
A test problem generator for large-scale unconstrained optimization