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No self-concordant barrier interior point method is strongly polynomial

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Résumé

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 ω(2n).

langue originaleAnglais
titreSTOC 2022 - Proceedings of the 54th Annual ACM SIGACT Symposium on Theory of Computing
rédacteurs en chefStefano Leonardi, Anupam Gupta
EditeurAssociation for Computing Machinery
Pages515-528
Nombre de pages14
ISBN (Electronique)9781450392648
Les DOIs
étatPublié - 6 sept. 2022
Evénement54th Annual ACM SIGACT Symposium on Theory of Computing, STOC 2022 - Rome, Italie
Durée: 20 juin 202224 juin 2022

Série de publications

NomProceedings of the Annual ACM Symposium on Theory of Computing
ISSN (imprimé)0737-8017

Une conférence

Une conférence54th Annual ACM SIGACT Symposium on Theory of Computing, STOC 2022
Pays/TerritoireItalie
La villeRome
période20/06/2224/06/22

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