Inexact subgradient methods for quasi-convex optimization problems
An inexact subgradient algorithm is proposed for the quasi-convex programming. We establish the convergence property, finite convergence and efficiency estimates. The Hlder condition is assumed instead of usc when the constraint set X is compact. The generalized weak sharp minima is introduced and utilized when X is noncompact. We apply the proposed algorithm to solve the CobbDouglas production efficiency problem.
subgradient method quasi-convex optimization weak sharp minima noise