In this paper, we design a class of infeasible interior-point methods for linear optimization based on large neighborhood. The algorithm is inspired by a full-Newton step infeasible algorithm with a linear convergence rate in problem dimension that was recently proposed by the second author. Unfortunately, despite its good numerical behavior, the theoretical convergence rate of our algorithm is worse up to square root of problem dimension.
Original languageEnglish
Pages (from-to)1-29
Number of pages29
JournalJournal of Optimization Theory and Applications
Issue number2
Publication statusPublished - 2015

    Research areas

  • Linear optimization, Oolynomial algorithms, Primal-dual infeasble interior-point methods

ID: 1724884