Deterministic (1/2 + {\epsilon})-Approximation for Submodular Maximization over a Matroid
Data Structures and Algorithms
2018-07-17 v1
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 + {\epsilon})-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.
Cite
@article{arxiv.1807.05532,
title = {Deterministic (1/2 + {\epsilon})-Approximation for Submodular Maximization over a Matroid},
author = {Niv Buchbinder and Moran Feldman and Mohit Garg},
journal= {arXiv preprint arXiv:1807.05532},
year = {2018}
}