# Approximability of convex programming (convex optimization)

Convex optimization is defined here: https://cstheory.stackexchange.com/questions/22314/definition-of-convex-optimization-problem-by-stephen-boyd-and-lieven-vandenbergh

But is anything known about the approximation complexity of the problem? Does it have a PTAS (poly time approximation scheme)? Or is there a proof that a PTAS is impossible unless P=NP? Are there any known results on upper/lower bounds on its approximability?

Any information will be much appreciated.

You haven't defined convex optimization in general, and indeed it is not clear how one would encode a general convex optimization problem. However, to answer your question it suffices to consider the special case of copositive programming. It is known that Independent Set can be expressed as a copositive program, and this problem is NP-hard to approximate up to a factor of $n^{1-\epsilon}$ for every $\epsilon > 0$. In particular, there is no PTAS.

• Thanks.. Let me check to make sure that the reduction from Ind.Set to Copositive Prog is an approximation preserving reduction. Jul 26, 2016 at 22:49