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The maximum Nash social welfare (NSW) -- which maximizes the geometric mean of agents' utilities -- is a fundamental solution concept with remarkable fairness and efficiency guarantees. The computational aspects of NSW have been extensively…

Computer Science and Game Theory · Computer Science 2023-12-15 Pallavi Jain , Rohit Vaish

This paper is merged with arXiv:2107.08965v2. We refer the reader to the full and updated version. We study the problem of allocating a set of indivisible goods among agents with 2-value additive valuations. Our goal is to find an…

Computer Science and Game Theory · Computer Science 2021-10-13 Hannaneh Akrami , Bhaskar Ray Chaudhury , Kurt Mehlhorn , Golnoosh Shahkarami , Quentin Vermande

We study the problem of approximating maximum Nash social welfare (NSW) when allocating m indivisible items among n asymmetric agents with submodular valuations. The NSW is a well-established notion of fairness and efficiency, defined as…

Computer Science and Game Theory · Computer Science 2020-01-01 Jugal Garg , Pooja Kulkarni , Rucha Kulkarni

We present a constant-factor approximation algorithm for the Nash social welfare maximization problem with subadditive valuations accessible via demand queries. More generally, we propose a template for NSW optimization by solving a…

Computer Science and Game Theory · Computer Science 2023-09-12 Shahar Dobzinski , Wenzheng Li , Aviad Rubinstein , Jan Vondrak

We study the problem of efficiently and fairly allocating a set of indivisible goods among agents with identical and additive valuations for the goods. The objective is to maximize the Nash social welfare, which is the geometric mean of the…

Data Structures and Algorithms · Computer Science 2022-01-06 Asei Inoue , Yusuke Kobayashi

For any $\varepsilon>0$, we give a simple, deterministic $(4+\varepsilon)$-approximation algorithm for the Nash social welfare (NSW) problem under submodular valuations. We also consider the asymmetric variant of the problem, where the…

Computer Science and Game Theory · Computer Science 2026-03-31 Jugal Garg , Edin Husić , Wenzheng Li , László A. Végh , Jan Vondrák

We study the problem of allocating indivisible goods among agents in a fair and economically efficient manner. In this context, the Nash social welfare-defined as the geometric mean of agents' valuations for their assigned bundles-stands as…

Computer Science and Game Theory · Computer Science 2021-10-27 Siddharth Barman , Paritosh Verma

We study the problem of fairly allocating a set of indivisible goods among agents with additive valuations. The extent of fairness of an allocation is measured by its Nash social welfare, which is the geometric mean of the valuations of the…

Computer Science and Game Theory · Computer Science 2018-07-23 Siddharth Barman , Sanath Kumar Krishnamurthy , Rohit Vaish

We consider the problem of approximating maximum Nash social welfare (NSW) while allocating a set of indivisible items to $n$ agents. The NSW is a popular objective that provides a balanced tradeoff between the often conflicting…

Computer Science and Game Theory · Computer Science 2020-10-02 Jugal Garg , Edin Husic , Laszlo A. Vegh

We consider the problem of locating a facility to serve a set of agents located along a line. The Nash welfare objective function, defined as the product of the agents' utilities, is known to provide a compromise between fairness and…

Computer Science and Game Theory · Computer Science 2023-10-09 Alexander Lam , Haris Aziz , Toby Walsh

We consider the problem of maximizing the Nash social welfare when allocating a set $\mathcal{G}$ of indivisible goods to a set $\mathcal{N}$ of agents. We study instances, in which all agents have 2-value additive valuations: The value of…

We study coverage problems in which, for a set of agents and a given threshold $T$, the goal is to select $T$ subsets (of the agents) that, while satisfying combinatorial constraints, achieve fair and efficient coverage among the agents. In…

Computer Science and Game Theory · Computer Science 2022-07-06 Siddharth Barman , Anand Krishna , Y. Narahari , Soumyarup Sadhukhan

We study the problem of allocating items to agents with submodular valuations with the goal of maximizing the weighted Nash social welfare (NSW). The best-known results for unweighted and weighted objectives are the $(4+\epsilon)$…

Computer Science and Game Theory · Computer Science 2025-11-06 Xiaohui Bei , Yuda Feng , Yang Hu , Shi Li , Ruilong Zhang

We study the Nash Social Welfare problem: Given $n$ agents with valuation functions $v_i:2^{[m]} \rightarrow {\mathbb R}$, partition $[m]$ into $S_1,\ldots,S_n$ so as to maximize $(\prod_{i=1}^{n} v_i(S_i))^{1/n}$. The problem has been…

Computer Science and Game Theory · Computer Science 2021-01-08 Wenzheng Li , Jan Vondrak

We study the problem of allocating a set of indivisible items to agents with supermodular utilities to maximize the Nash social welfare. We show that the problem is NP-hard for any approximation factor.

Computer Science and Game Theory · Computer Science 2025-10-31 Alon Bebchuk

We study the problem of allocating indivisible goods among $n$ agents with the objective of maximizing Nash social welfare (NSW). This welfare function is defined as the geometric mean of the agents' valuations and, hence, it strikes a…

Computer Science and Game Theory · Computer Science 2022-07-18 Siddharth Barman , Anand Krishna , Pooja Kulkarni , Shivika Narang

We study the problem of maximizing Nash welfare (MNW) while allocating indivisible goods to asymmetric agents. The Nash welfare of an allocation is the weighted geometric mean of agents' utilities, and the allocation with maximum Nash…

Computer Science and Game Theory · Computer Science 2022-05-02 Jugal Garg , Edin Husić , Aniket Murhekar , László Végh

The maximization of Nash welfare, which equals the geometric mean of agents' utilities, is widely studied because it balances efficiency and fairness in resource allocation problems. Banerjee, Gkatzelis, Gorokh, and Jin (2022) recently…

Data Structures and Algorithms · Computer Science 2024-11-11 Zhiyi Huang , Minming Li , Xinkai Shu , Tianze Wei

We study the problem of assigning items to agents so as to maximize the \emph{weighted} Nash Social Welfare (NSW) under submodular valuations. The best-known result for the problem is an $O(nw_{\max})$-approximation due to Garg, Husic, Li,…

Computer Science and Game Theory · Computer Science 2025-11-05 Yuda Feng , Yang Hu , Shi Li , Ruilong Zhang

We study the problem of allocating indivisible goods among agents that have an identical subadditive valuation over the goods. The extent of fairness and efficiency of allocations is measured by the generalized means of the values that the…

Computer Science and Game Theory · Computer Science 2020-05-04 Siddharth Barman , Ranjani G. Sundaram
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