Convergent conic linear programming relaxations for cone convex polynomial programs

In this paper we show that a hierarchy of conic linear programming relaxations of a cone-convex polynomial programming problem converges asymptotically under a mild well-posedness condition which can easily be checked numerically for polynomials. We also establish that an additional qualification condition guarantees finite convergence of the hierarchy. Consequently, we derive convergent semi-definite programming relaxations for convex matrix polynomial programs as well as easily tractable conic linear programming relaxations for a class of pth-order cone convex polynomial programs.