Deterministic \(\boldsymbol{(\unicode{x00BD}+\varepsilon)}\) -Approximation for Submodular Maximization over a Matroid.

Niv Buchbinder, Moran Feldman, Mohit Garg

Research output: Contribution to journalArticlepeer-review


We study the problem of maximizing a monotone submodular function subject to a matroid constraint and present a deterministic algorithm that achieves (1/2+ϵ)-approximation for the problem (for some ϵ ≥ 8 10-4). This algorithm is the first deterministic algorithm known to improve over the 1/2-approximation ratio of the classical greedy algorithm proved by Nemhauser, Wolsey, and Fisher in 1978.

Original languageEnglish
Pages (from-to)945-967
Number of pages23
JournalSIAM Journal on Computing
Issue number4
StatePublished - 2023
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2023 Niv Buchbinder.


  • deterministic algorithms
  • matroid
  • submodular optimization

ASJC Scopus subject areas

  • General Computer Science
  • General Mathematics


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