Deterministic (1/2 + ε)-approximation for submodular maximization over a matroid

Niv Buchbinder, Moran Feldman, Mohit Garg

Research output: Contribution to conferencePaperpeer-review

36 Scopus citations

Abstract

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. This algorithm is the first deterministic algorithm known to improve over the 1/2-approximation ratio of the classical greedy algorithm proved by Nemhauser, Wolsely and Fisher in 1978.

Original languageEnglish
Pages241-254
Number of pages14
StatePublished - 2019
Event30th Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2019 - San Diego, United States
Duration: 6 Jan 20199 Jan 2019

Conference

Conference30th Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2019
Country/TerritoryUnited States
CitySan Diego
Period6/01/199/01/19

Funding

FundersFunder number
Israel Science Foundation1585/15, 1357/16

    Keywords

    • Deterministic algorithms
    • Matroid
    • Submodular optimization

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