Incremental Submodular Maximization: Better Than Greedy
Data Structures and Algorithms
2026-06-26 v1
Abstract
We consider submodular maximization under increasing cardinality constraint and ask for a good incremental solution, i.e., an ordering of the ground set such that each prefix of the ordering yields a good solution for its respective cardinality. A classical result in this setting is that the greedy algorithm achieves a competitive ratio, i.e., an approximation guarantee across all cardinalities, of . No better general guarantee was previously known. We present an adaptive scaling algorithm achieving a competitive ratio of . We complement our result by a deterministic lower bound of on the best possible competitive ratio for incremental submodular maximization.
Cite
@article{arxiv.2606.28558,
title = {Incremental Submodular Maximization: Better Than Greedy},
author = {Marcin Bienkowski and Joakim Blikstad and Jarosław Byrka and Martín Costa and Yann Disser and Annette Lutz},
journal= {arXiv preprint arXiv:2606.28558},
year = {2026}
}