A strongly polynomial algorithm for linear programs with at most two nonzero entries per row or column

Dadush, Daniel, Koh, Zhuan Khye, Natura, Bento, Olver, Neil ORCID: 0000-0001-8897-5459 and Végh, László A. ORCID: 0000-0003-1152-200X (2024) A strongly polynomial algorithm for linear programs with at most two nonzero entries per row or column. In: Mohar, Bojan, Shinkar, Igor and O�Donnell, Ryan, (eds.) STOC 2024: Proceedings of the 56th Annual ACM Symposium on Theory of Computing (STOC ’24), June 24–28. Proceedings of the Annual ACM Symposium on Theory of Computing. ACM Press, New York, NY, 1561 – 1572. ISBN 9798400703836

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Abstract

We give a strongly polynomial algorithm for minimum cost generalized flow, and hence for optimizing any linear program with at most two non-zero entries per row, or at most two non-zero entries per column. Primal and dual feasibility were shown by Végh (MOR ’17) and Megiddo (SICOMP ’83), respectively. Our result can be viewed as progress towards understanding whether all linear programs can be solved in strongly polynomial time, also referred to as Smale’s 9th problem. Our approach is based on the recent primal-dual interior point method (IPM) by Allamigeon, Dadush, Loho, Natura, and Végh (FOCS ’22). The number of iterations needed by the IPM is bounded, up to a polynomial factor in the number of inequalities, by the straight line complexity of the central path. Roughly speaking, this is the minimum number of pieces of any piecewise linear curve that multiplicatively approximates the central path. As our main contribution, we show that the straight line complexity of any minimum cost generalized flow instance is polynomial in the number of arcs and vertices. By applying a reduction of Hochbaum (ORL ’04), the same bound applies to any linear program with at most two non-zeros per column or per row. To be able to run the IPM, one requires a suitable initial point. For this purpose, we develop a novel multistage approach, where each stage can be solved in strongly polynomial time given the result of the previous stage. Beyond this, substantial work is needed to ensure that the bit complexity of each iterate remains bounded during the execution of the algorithm. For this purpose, we show that one can maintain a representation of the iterates as a low complexity convex combination of vertices and extreme rays. Our approach is black-box and can be applied to any log-barrier path-following method.

Item Type:	Book Section
Official URL:	https://dl.acm.org/doi/proceedings/10.1145/3618260
Additional Information:	© 2024 The Author(s)
Divisions:	Mathematics
Subjects:	Q Science > QA Mathematics
Date Deposited:	08 Apr 2024 15:48
Last Modified:	11 Jul 2024 20:00
URI:	http://eprints.lse.ac.uk/id/eprint/122569

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