Dual conditions characterizing optimality for convex multi-objective programs

Asymptotic necessary and sufficient conditions for a point to be a Pareto m inimum, and weak minimum (proper minimum) for a convex multi-objective prog ram are given without a regularity condition. It is further shown that, in the cases of weak minimum and single objective function, the asymptotic dua l conditions reduce to nonasymptotic optimality conditions under Slater's c onstraint qualification. The results are applied to multi-objective quadrat ic and linar programming problems. Numerical examples are given to illustra te the nature of the conditions.