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Single-Source Unsplittable Flows in Planar Graphs


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Date

2024

Publication Type

Conference Paper

ETH Bibliography

yes

Citations

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Abstract

The single-source unsplittable flow (SSUF) problem asks to send flow from a common source to different terminals with unrelated demands, each terminal being served through a single path. One of the most heavily studied SSUF objectives is to minimize the violation of some given arc capacities. A seminal result of Dinitz, Garg, and Goemans showed that, whenever a fractional flow exists respecting the capacities, then there is an unsplittable one violating the capacities by at most the maximum demand. Goemans conjectured a very natural cost version of the same result, where the unsplittable flow is required to be no more expensive than the fractional one. This intriguing conjecture remains open. More so, there are arguably no non-trivial graph classes for which it is known to hold. We show that a slight weakening of it (with at most twice as large violations) holds for planar graphs. Our result is based on a connection to a highly structured discrepancy problem, whose repeated resolution allows us to successively reduce the number of paths used for each terminal, until we obtain an unsplittable flow. Moreover, our techniques also extend to simultaneous upper and lower bounds on the flow values. This also affirmatively answers a conjecture of Morell and Skutella for planar SSUF.

Publication status

published

Book title

Proceedings of the 2024 Annual ACM-SIAM Symposium on Discrete Algorithms (SODA)

Journal / series

Volume

Pages / Article No.

639 - 668

Publisher

SIAM

Event

35th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA 2024)

Edition / version

Methods

Software

Geographic location

Date collected

Date created

Subject

Organisational unit

09487 - Zenklusen, Rico / Zenklusen, Rico check_circle

Notes

Funding

184622 - Toward Stronger Approximation Algorithms for Fundamental Network Design and Optimization Problems (SNF)
817750 - Fundamental Problems at the Interface of Combinatorial Optimization with Integer Programming and Online Optimization (EC)

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