Necessary conditions for an extremum and an inverse function theorem without a priori normality assumptions

A smooth optimization problem, involving a finite number of constraints and a convex cone inclusion constraint, is considered. First and second order, necessary and sufficient, optimality conditions at points which may not satisfy Robinson's constraint qualification are derived. As a consequence of the obtained results, a variant of the inverse function theorem, at such points, is obtained.