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We study the problem of allocating a set of indivisible items to agents with additive utilities to maximize the Nash social welfare. Cole and Gkatzelis recently proved that this problem admits a constant factor approximation. We complement…

计算复杂性 · 计算机科学 2015-07-07 Euiwoong Lee

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…

计算机科学与博弈论 · 计算机科学 2020-01-01 Jugal Garg , Pooja Kulkarni , Rucha Kulkarni

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 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…

计算机科学与博弈论 · 计算机科学 2021-01-08 Wenzheng Li , Jan Vondrak

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…

计算机科学与博弈论 · 计算机科学 2021-10-13 Hannaneh Akrami , Bhaskar Ray Chaudhury , Kurt Mehlhorn , Golnoosh Shahkarami , Quentin Vermande

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…

计算机科学与博弈论 · 计算机科学 2018-07-23 Siddharth Barman , Sanath Kumar Krishnamurthy , Rohit Vaish

We study the problem of allocating a set of indivisible goods among a set of agents with \emph{2-value additive valuations}. In this setting, each good is valued either $1$ or $p/q$, for some fixed co-prime numbers $p,q\in \mathbb{N}$ such…

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…

计算机科学与博弈论 · 计算机科学 2026-03-31 Jugal Garg , Edin Husić , Wenzheng Li , László A. Végh , Jan Vondrák

We study the problem of maximizing Nash social welfare, which is the geometric mean of agents' utilities, in two well-known models. The first model involves one-sided preferences, where a set of indivisible items is allocated among a group…

计算机科学与博弈论 · 计算机科学 2025-05-19 Salil Gokhale , Harshul Sagar , Rohit Vaish , Vignesh Viswanathan , Jatin Yadav

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…

数据结构与算法 · 计算机科学 2022-01-06 Asei Inoue , Yusuke Kobayashi

We present a $380$-approximation algorithm for the Nash Social Welfare problem with submodular valuations. Our algorithm builds on and extends a recent constant-factor approximation for Rado valuations.

计算机科学与博弈论 · 计算机科学 2021-11-18 Wenzheng Li , 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…

计算机科学与博弈论 · 计算机科学 2021-10-27 Siddharth Barman , Paritosh Verma

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 $(4+\epsilon)$…

计算机科学与博弈论 · 计算机科学 2025-11-06 Xiaohui Bei , Yuda Feng , Yang Hu , Shi Li , Ruilong Zhang

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…

计算机科学与博弈论 · 计算机科学 2023-09-12 Shahar Dobzinski , Wenzheng Li , Aviad Rubinstein , Jan Vondrak

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…

计算机科学与博弈论 · 计算机科学 2023-12-15 Pallavi Jain , Rohit Vaish

We consider the problem of dividing a set of indivisible goods among agents with additive valuations. This problem has been studied under various objectives in both the computer science and the operations research literature. Our main…

计算机科学与博弈论 · 计算机科学 2026-05-27 Vignesh Viswanathan

We consider the task of assigning indivisible goods to a set of agents in a fair manner. Our notion of fairness is Nash social welfare, i.e., the goal is to maximize the geometric mean of the utilities of the agents. Each good comes in…

数据结构与算法 · 计算机科学 2019-05-13 Bhaskar Chaudhury , Yun Kuen Cheung , Jugal Garg , Naveen Garg , Martin Hoefer , Kurt Mehlhorn

We develop polynomial-time algorithms for the fair and efficient allocation of indivisible goods among $n$ agents that have subadditive valuations over the goods. We first consider the Nash social welfare as our objective and design a…

计算机科学与博弈论 · 计算机科学 2020-07-07 Siddharth Barman , Umang Bhaskar , Anand Krishna , Ranjani G. Sundaram

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,…

计算机科学与博弈论 · 计算机科学 2025-11-05 Yuda Feng , Yang Hu , Shi Li , Ruilong Zhang

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…

计算机科学与博弈论 · 计算机科学 2023-10-09 Alexander Lam , Haris Aziz , Toby Walsh
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