Asymptotic Dual Conditions Characterizing Optimality for Infinite Convex Programs

Characterizations of optimality are presented for infinite-dimensional convex programming problems, where the number of constraints is not restricted to be finite and where no constraint qualification is assumed. The optimality conditions are given in asymptotic forms using subdifferentials and €-subdifferentials. They are obtained by employing a version of the Farkas lemma for systems involving convex functions. An extension of the results to problems with a semiconvex objective function is also given.