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Nash Social Welfare for 2-value Instances

MPS-Authors
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Akrami,  Hannaneh
Algorithms and Complexity, MPI for Informatics, Max Planck Society;

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Ray Chaudhury,  Bhaskar
Algorithms and Complexity, MPI for Informatics, Max Planck Society;

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Mehlhorn,  Kurt
Algorithms and Complexity, MPI for Informatics, Max Planck Society;

/persons/resource/persons251338

Shahkarami,  Golnoosh
Algorithms and Complexity, MPI for Informatics, Max Planck Society;

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arXiv:2106.14816.pdf
(Preprint), 222KB

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Citation

Akrami, H., Ray Chaudhury, B., Mehlhorn, K., Shahkarami, G., & Vermande, Q. (2021). Nash Social Welfare for 2-value Instances. Retrieved from https://arxiv.org/abs/2106.14816.


Cite as: https://hdl.handle.net/21.11116/0000-0008-DB45-4
Abstract
We study the problem of allocating a set of indivisible goods among agents
with 2-value additive valuations. Our goal is to find an allocation with
maximum Nash social welfare, i.e., the geometric mean of the valuations of the
agents. We give a polynomial-time algorithm to find a Nash social welfare
maximizing allocation when the valuation functions are integrally 2-valued,
i.e., each agent has a value either $1$ or $p$ for each good, for some positive
integer $p$. We then extend our algorithm to find a better approximation factor
for general 2-value instances.