It is an open question to determine if the theory of self-concordant barriers can provide an interior point method with strongly polynomial complexity in linear programming. In the special case of the logarithmic barrier, it was shown in [Allamigeon, Benchimol, Gaubert and Joswig, SIAM J. on Applied Algebra and Geometry, 2018] that the answer is negative. In this paper, we show that none of the self-concordant barrier interior point methods is strongly polynomial. This result is obtained by establishing that, on parametric families of convex optimization problems, the log-limit of the central path degenerates to a piecewise linear curve, independently of the choice of the barrier function. We provide an explicit linear program that falls in the same class as the Klee-Minty counterexample, i.e., in dimension $n$ with $2n$ constraints, in which the number of iterations is $\Omega(2^n)$.
翻译:在线性编程中,要确定自相兼容屏障理论能否提供具有强烈多元复杂性的内部点方法,这是一个有待解决的问题。在对数屏障的特殊情况中,[Allamigeon、Bencimol、Gaubert和Joswig,SIM J.关于应用代数和几何,2018年]显示答案是否定的。在本文中,我们显示自相兼容的屏障内点方法没有一个是强烈多元的。这一结果通过确定,在对等优化问题的对等组别上,中央路径的日志界限会退化为一条支线曲线,与屏障功能的选择无关。我们提供了一个明确的线性程序,它与Klee-Minty反example同,即,在有2美元约束的维面上,也就是在2美元的维值上,其中间值是$\Omega(2n)美元。