No Self-Concordant Barrier Interior Point Method Is Strongly Polynomial
PROCEEDINGS OF THE 54TH ANNUAL ACM SIGACT SYMPOSIUM ON THEORY OF COMPUTING (STOC '22)(2022)
摘要
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 for the simplex method, i.e., in which the feasible region is a combinatorial cube and the number of iterations is O(2(n)).
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关键词
Interior point methods, self-concordant barriers, linear programming, convex programming, tropical geometry
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