English

Maximizing Nash Social Welfare in 2-Value Instances

Computer Science and Game Theory 2021-10-04 v2

Abstract

We consider the problem of maximizing the Nash social welfare when allocating a set G\mathcal{G} of indivisible goods to a set N\mathcal{N} of agents. We study instances, in which all agents have 2-value additive valuations: The value of every agent iNi \in \mathcal{N} for every good jGj \in \mathcal{G} is vij{p,q}v_{ij} \in \{p,q\}, for p,qNp,q \in \mathbb{N}, pqp \le q. Maybe surprisingly, we design an algorithm to compute an optimal allocation in polynomial time if pp divides qq, i.e., when p=1p=1 and qNq \in \mathbb{N} after appropriate scaling. The problem is \classNP-hard whenever pp and qq are coprime and p3p \ge 3. In terms of approximation, we present positive and negative results for general pp and qq. We show that our algorithm obtains an approximation ratio of at most 1.0345. Moreover, we prove that the problem is \classAPX-hard, with a lower bound of 1.0000151.000015 achieved at p/q=4/5p/q = 4/5.

Keywords

Cite

@article{arxiv.2107.08965,
  title  = {Maximizing Nash Social Welfare in 2-Value Instances},
  author = {Hannaneh Akrami and Bhaskar Ray Chaudhury and Martin Hoefer and Kurt Mehlhorn and Marco Schmalhofer and Golnoosh Shahkarami and Giovanna Varricchio and Quentin Vermande and Ernest van Wijland},
  journal= {arXiv preprint arXiv:2107.08965},
  year   = {2021}
}
R2 v1 2026-06-24T04:19:46.302Z