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Approximating the Nash Social Welfare with Indivisible Items

Published: 14 June 2015 Publication History

Abstract

We study the problem of allocating a set of indivisible items among agents with additive valuations, with the goal of maximizing the geometric mean of the agents' valuations, i.e., the Nash social welfare. This problem is known to be NP-hard, and our main result is the first efficient constant-factor approximation algorithm for this objective. We first observe that the integrality gap of the natural fractional relaxation is exponential, so we propose a different fractional allocation which implies a tighter upper bound and, after appropriate rounding, yields a good integral allocation.
An interesting contribution of this work is the fractional allocation that we use. The relaxation of our problem can be solved efficiently using the Eisenberg-Gale program, whose optimal solution can be interpreted as a market equilibrium with the dual variables playing the role of item prices. Using this market-based interpretation, we define an alternative equilibrium allocation where the amount of spending that can go into any given item is bounded, thus keeping the highly priced items under-allocated, and forcing the agents to spend on lower priced items. The resulting equilibrium prices reveal more information regarding how to assign items so as to obtain a good integral allocation.

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    cover image ACM Conferences
    STOC '15: Proceedings of the forty-seventh annual ACM symposium on Theory of Computing
    June 2015
    916 pages
    ISBN:9781450335362
    DOI:10.1145/2746539
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 14 June 2015

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    Author Tags

    1. approximation algorithms
    2. fair division
    3. geometric mean
    4. nash bargaining
    5. nash product
    6. nash social welfare

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    STOC '15: Symposium on Theory of Computing
    June 14 - 17, 2015
    Oregon, Portland, USA

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    STOC '15 Paper Acceptance Rate 93 of 347 submissions, 27%;
    Overall Acceptance Rate 1,469 of 4,586 submissions, 32%

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    • (2024)Maximizing Nash Social Welfare Based on Greedy Algorithm and Estimation of Distribution AlgorithmBiomimetics10.3390/biomimetics91106529:11(652)Online publication date: 24-Oct-2024
    • (2024)Maximum Nash Social Welfare Under Budget-Feasible EFXIEEE Transactions on Network Science and Engineering10.1109/TNSE.2023.333210411:2(1810-1820)Online publication date: Mar-2024
    • (2023)A Meta-heuristic Approach for Strategic Fair Division ProblemsProceedings of the 2023 7th International Conference on Intelligent Systems, Metaheuristics & Swarm Intelligence10.1145/3596947.3596969(87-94)Online publication date: 23-Apr-2023
    • (2023)Fairness and Incentive Compatibility via Percentage FeesProceedings of the 24th ACM Conference on Economics and Computation10.1145/3580507.3597810(517-535)Online publication date: 9-Jul-2023
    • (2023)Fair Multi-Resource Allocation in Heterogeneous Servers With an External Resource TypeIEEE/ACM Transactions on Networking10.1109/TNET.2022.321342631:3(1244-1262)Online publication date: Jun-2023
    • (2023)Computing fair and efficient allocations with few utility valuesTheoretical Computer Science10.1016/j.tcs.2023.113932962(113932)Online publication date: Jun-2023
    • (2023)Fairness criteria for allocating indivisible chores: connections and efficienciesAutonomous Agents and Multi-Agent Systems10.1007/s10458-023-09618-537:2Online publication date: 31-Aug-2023
    • (2023)Online Nash Welfare Maximization Without PredictionsWeb and Internet Economics10.1007/978-3-031-48974-7_23(402-419)Online publication date: 31-Dec-2023
    • (2023)EFX Under Budget ConstraintFrontiers of Algorithmic Wisdom10.1007/978-3-031-20796-9_1(3-14)Online publication date: 1-Jan-2023
    • (2022)Determinant Maximization via Matroid Intersection Algorithms2022 IEEE 63rd Annual Symposium on Foundations of Computer Science (FOCS)10.1109/FOCS54457.2022.00031(255-266)Online publication date: Oct-2022
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