Maximizing Nash Social Welfare in 2-Value Instances
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Abstract (arXiv)
We consider the problem of maximizing the Nash social welfare when allocating a set G of indivisible goods to a set N of agents. We study instances, in which all agents have 2-value additive valuations: The value of every agent i ∈ N for every good j ∈ G is vij ∈ p,q, for p,q ∈ mathbbN, p ≤ q. Maybe surprisingly, we design an algorithm to compute an optimal allocation in polynomial time if p divides q, i.e., when p=1 and q ∈ mathbbN after appropriate scaling. The problem is classNP-hard whenever p and q are coprime and p ≥ 3. In terms of approximation, we present positive and negative results for general p and q. 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 1.000015 achieved at p/q = 4/5.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 19 Jul 2021.
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Citing papers per year: 2023: 1; 2024: 0; 2025: 3.
4 papers.
- 2025Online Fair Division for Personalized 2-Value Instancescited by 3
- 2023Dividing Good and Better Items Among Agents with Bivalued Submodular Valuationscited by 0
- 2025Large-Scale Auto-bidding with Nash Equilibrium Constraintscited by 0
- 2025Probing EFX via PMMS: (Non-)Existence Results in Discrete Fair Divisioncited by 0
- 2025Probing EFX via PMMS: (Non-)Existence Results in Discrete Fair Division20 Jul 2025
- 2025Online Fair Division for Personalized 2-Value Instances28 May 2025
- 2025Large-Scale Auto-bidding with Nash Equilibrium Constraints13 Mar 2025
- 2023Dividing Good and Better Items Among Agents with Bivalued Submodular Valuations6 Feb 2023