  We present new results on optimization problems where the involved functions
are evenly convex. By means of a generalized conjugation scheme and the
perturbation theory introduced by Rockafellar, we propose an alternative dual
problem for a general optimization one defined on a separated locally convex
topological space. Sufficient conditions for converse and total duality
involving the even convexity of the perturbation function and
$c$-subdifferentials are given. Formulae for the $c$-subdifferential and
biconjugate of the objective function of a general optimization problem are
provided, too. We also characterize the total duality also by means of the
saddle-point theory for a notion of Lagrangian adapted to the considered
framework.
