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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

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 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…

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

Recently Cole and Gkatzelis gave the first constant factor approximation algorithm for the problem of allocating indivisible items to agents, under additive valuations, so as to maximize the Nash Social Welfare. We give constant factor…

计算机科学与博弈论 · 计算机科学 2017-04-10 Nima Anari , Tung Mai , Shayan Oveis Gharan , Vijay V. Vazirani

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…

计算机科学与博弈论 · 计算机科学 2020-10-02 Jugal Garg , Edin Husic , Laszlo A. Vegh

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

We study the problem of fair allocation of a set of indivisible items among agents with additive valuations, under matroid constraints and two generalizations: $p$-extendible system and independence system constraints. The objective is to…

计算机科学与博弈论 · 计算机科学 2024-11-07 Yuanyuan Wang , Xin Chen , Qingqin Nong

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

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 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 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 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 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

A set of $m$ indivisible goods is to be allocated to a set of $n$ agents. Each agent $i$ has an additive valuation function $v_i$ over goods. The value of a good $g$ for agent $i$ is either $1$ or $s$, where $s$ is a fixed rational number…

计算机科学与博弈论 · 计算机科学 2026-02-23 Kurt Mehlhorn

We propose a new convex programming relaxation for the weighted Nash social welfare (NSW) problem that achieves a matching $(e^{1/e}\approx 1.445)$-approximation via the rounding algorithm of Feng and Li. Unlike the exponential-size…

数据结构与算法 · 计算机科学 2026-04-28 Yuda Feng , Weijiang Hu , Shi Li

In an instance of the weighted Nash Social Welfare problem, we are given a set of $m$ indivisible items, $\mathscr{G}$, and $n$ agents, $\mathscr{A}$, where each agent $i \in \mathscr{A}$ has a valuation $v_{ij}\geq 0$ for each item $j\in…

数据结构与算法 · 计算机科学 2024-01-08 Adam Brown , Aditi Laddha , Madhusudhan Reddy Pittu , Mohit Singh

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 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…

计算机科学与博弈论 · 计算机科学 2022-07-06 Siddharth Barman , Anand Krishna , Y. Narahari , Soumyarup Sadhukhan
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