A new primal-dual interior-point method for semidefinite optimization based on a new wide neighbourhood with infinity-norm

In this paper, we present a new primal-dual interior-point algorithm based on a new large neighborhood N for semidefinite optimization. This large neighborhood is based on the infinity norm. It is larger than the ) , ( N large neighborhood of the central path, which is popular wideneighborhood. We demonstrate the convergence of the proposed algorithm and show that the algorithm has iteration complexity bound for the Nesterov-Todd direction.

Keywords:

Semidefinite optimization , wide neighborhood , interiorpoint method , iteration complexity bound.