On Maximum Weighted Nash Welfare for Binary Valuations
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Abstract (arXiv)
We consider the problem of fairly allocating indivisible goods to agents with weights representing their entitlements. A natural rule in this setting is the maximum weighted Nash welfare (MWNW) rule, which selects an allocation maximizing the weighted product of the agents' utilities. We show that when agents have binary valuations, a specific version of MWNW is resource- and population-monotone, satisfies group-strategyproofness, and can be implemented in polynomial time.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 8 Apr 2022.
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Citing papers per year: 2022: 1; 2023: 0; 2024: 1; 2025: 4.
6 papers.
- 2024Temporal Fair Division of Indivisible Itemscited by 11
- 2025Online Fair Division with Additional Informationcited by 6
- 2025Not in My Backyard! Temporal Voting Over Public Chorescited by 6
- 2022Yankee Swap: a Fast and Simple Fair Allocation Mechanism for Matroid Rank Valuationscited by 3
- 2025Understanding EFX Allocations: Counting and Variantscited by 3
- 2025Fairness in Repeated Matching: A Maximin Perspectivecited by 2
- 2025Fairness in Repeated Matching: A Maximin Perspective6 Oct 2025
- 2025Not in My Backyard! Temporal Voting Over Public Chores12 Aug 2025
- 2025Online Fair Division with Additional Information30 May 2025
- 2025Understanding EFX Allocations: Counting and Variants4 Apr 2025
- 2024Temporal Fair Division of Indivisible Items18 Oct 2024
- 2022Yankee Swap: a Fast and Simple Fair Allocation Mechanism for Matroid Rank Valuations17 Jun 2022