Abstract
In this paper, we present a corrector–predictor path-following interior-point method for second-order cone optimization (SOCO) based on a new proximity measure. The algorithm produces a sequence of iterates in a neighbourhood of the central path based on a new proximity measure. We show that the algorithm is well-defined and derive the complexity bound for the algorithm. We obtain the best-known result for SOCO. The numerical results show that the proposed algorithm is effective.
Full Text
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call