In this paper, we revisit the main principles for constructing polynomial-time primal-dual interior-point algorithms (IPAs). Starting from the break-through paper by Gonzaga (1989), their development was related to the barrier methods, where the objective function was added to the barrier for...

In this paper, we suggest a new interior-point method for linear optimization, based on the idea of Parabolic Target Space. Our method can start at any strictly feasible primal-dual pair and go directly towards a solution by a predictor-corrector scheme. Each iteration needs inversion of a...

In this paper, we propose new linearly convergent second-order methods for minimizing convex quartic polynomials. This framework is applied for designing optimization schemes, which can solve general convex problems satisfying a new condition of quartic regularity. It assumes positive...