Negative-Weight Single-Source Shortest Paths in Near-linear Time

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Standard

Negative-Weight Single-Source Shortest Paths in Near-linear Time. / Bernstein, Aaron; Nanongkai, Danupon; Wulff-Nilsen, Christian.

2022 IEEE 63rd Annual Symposium on Foundations of Computer Science (FOCS). IEEE, 2022. p. 600-611 (Annual IEEE Symposium on Foundations of Computer Science).

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Harvard

Bernstein, A, Nanongkai, D & Wulff-Nilsen, C 2022, Negative-Weight Single-Source Shortest Paths in Near-linear Time. in 2022 IEEE 63rd Annual Symposium on Foundations of Computer Science (FOCS). IEEE, Annual IEEE Symposium on Foundations of Computer Science, pp. 600-611, 63rd Annual IEEE Symposium on Foundations of Computer Science (FOCS), Denver, Colombia, 31/10/2022. https://doi.org/10.1109/FOCS54457.2022.00063

APA

Bernstein, A., Nanongkai, D., & Wulff-Nilsen, C. (2022). Negative-Weight Single-Source Shortest Paths in Near-linear Time. In 2022 IEEE 63rd Annual Symposium on Foundations of Computer Science (FOCS) (pp. 600-611). IEEE. Annual IEEE Symposium on Foundations of Computer Science https://doi.org/10.1109/FOCS54457.2022.00063

Vancouver

Bernstein A, Nanongkai D, Wulff-Nilsen C. Negative-Weight Single-Source Shortest Paths in Near-linear Time. In 2022 IEEE 63rd Annual Symposium on Foundations of Computer Science (FOCS). IEEE. 2022. p. 600-611. (Annual IEEE Symposium on Foundations of Computer Science). https://doi.org/10.1109/FOCS54457.2022.00063

Author

Bernstein, Aaron ; Nanongkai, Danupon ; Wulff-Nilsen, Christian. / Negative-Weight Single-Source Shortest Paths in Near-linear Time. 2022 IEEE 63rd Annual Symposium on Foundations of Computer Science (FOCS). IEEE, 2022. pp. 600-611 (Annual IEEE Symposium on Foundations of Computer Science).

Bibtex

@inproceedings{75677331afea48668b5a25e7fa89e29a,
title = "Negative-Weight Single-Source Shortest Paths in Near-linear Time",
abstract = "We present a randomized algorithm that computes single-source shortest paths (SSSP) in O(mlog(8)(n) logW) time when edge weights are integral and can be negative. This essentially resolves the classic negative-weight SSSP problem. The previous bounds are (O) over tilde ((m + n(1.5)) logW) [BLNPSSSW FOCS'20] and m(4/3+o(1)) logW [AMV FOCS'20]. Near-linear time algorithms were known previously only for the special case of planar directed graphs [Fakcharoenphol and Rao FOCS'01]. In contrast to all recent developments that rely on sophisticated continuous optimization methods and dynamic algorithms, our algorithm is simple: it requires only a simple graph decomposition and elementary combinatorial tools. In fact, ours is the first combinatorial algorithm for negative-weight SSSP to break through the classic (O) over tilde (m root n logW) bound from over three decades ago [Gabow and Tarjan SICOMP'89].",
keywords = "graphs and networks, path and circuit problems, graph algorithms, analysis of algorithms, SCALING ALGORITHMS, GRAPHS",
author = "Aaron Bernstein and Danupon Nanongkai and Christian Wulff-Nilsen",
year = "2022",
doi = "10.1109/FOCS54457.2022.00063",
language = "English",
series = "Annual IEEE Symposium on Foundations of Computer Science",
pages = "600--611",
booktitle = "2022 IEEE 63rd Annual Symposium on Foundations of Computer Science (FOCS)",
publisher = "IEEE",
note = "63rd Annual IEEE Symposium on Foundations of Computer Science (FOCS) ; Conference date: 31-10-2022 Through 03-11-2022",

}

RIS

TY - GEN

T1 - Negative-Weight Single-Source Shortest Paths in Near-linear Time

AU - Bernstein, Aaron

AU - Nanongkai, Danupon

AU - Wulff-Nilsen, Christian

PY - 2022

Y1 - 2022

N2 - We present a randomized algorithm that computes single-source shortest paths (SSSP) in O(mlog(8)(n) logW) time when edge weights are integral and can be negative. This essentially resolves the classic negative-weight SSSP problem. The previous bounds are (O) over tilde ((m + n(1.5)) logW) [BLNPSSSW FOCS'20] and m(4/3+o(1)) logW [AMV FOCS'20]. Near-linear time algorithms were known previously only for the special case of planar directed graphs [Fakcharoenphol and Rao FOCS'01]. In contrast to all recent developments that rely on sophisticated continuous optimization methods and dynamic algorithms, our algorithm is simple: it requires only a simple graph decomposition and elementary combinatorial tools. In fact, ours is the first combinatorial algorithm for negative-weight SSSP to break through the classic (O) over tilde (m root n logW) bound from over three decades ago [Gabow and Tarjan SICOMP'89].

AB - We present a randomized algorithm that computes single-source shortest paths (SSSP) in O(mlog(8)(n) logW) time when edge weights are integral and can be negative. This essentially resolves the classic negative-weight SSSP problem. The previous bounds are (O) over tilde ((m + n(1.5)) logW) [BLNPSSSW FOCS'20] and m(4/3+o(1)) logW [AMV FOCS'20]. Near-linear time algorithms were known previously only for the special case of planar directed graphs [Fakcharoenphol and Rao FOCS'01]. In contrast to all recent developments that rely on sophisticated continuous optimization methods and dynamic algorithms, our algorithm is simple: it requires only a simple graph decomposition and elementary combinatorial tools. In fact, ours is the first combinatorial algorithm for negative-weight SSSP to break through the classic (O) over tilde (m root n logW) bound from over three decades ago [Gabow and Tarjan SICOMP'89].

KW - graphs and networks

KW - path and circuit problems

KW - graph algorithms

KW - analysis of algorithms

KW - SCALING ALGORITHMS

KW - GRAPHS

U2 - 10.1109/FOCS54457.2022.00063

DO - 10.1109/FOCS54457.2022.00063

M3 - Article in proceedings

T3 - Annual IEEE Symposium on Foundations of Computer Science

SP - 600

EP - 611

BT - 2022 IEEE 63rd Annual Symposium on Foundations of Computer Science (FOCS)

PB - IEEE

T2 - 63rd Annual IEEE Symposium on Foundations of Computer Science (FOCS)

Y2 - 31 October 2022 through 3 November 2022

ER -

ID: 337602711