Simplification and improvement of MMS approximation

H Akrami, J Garg, E Sharma, S Taki - arXiv preprint arXiv:2303.16788, 2023 - arxiv.org
arXiv preprint arXiv:2303.16788, 2023arxiv.org
We consider the problem of fairly allocating a set of indivisible goods among $ n $ agents
with additive valuations, using the popular fairness notion of maximin share (MMS). Since
MMS allocations do not always exist, a series of works provided existence and algorithms for
approximate MMS allocations. The Garg-Taki algorithm gives the current best approximation
factor of $(\frac {3}{4}+\frac {1}{12n}) $. Most of these results are based on complicated
analyses, especially those providing better than $2/3$ factor. Moreover, since no tight …
We consider the problem of fairly allocating a set of indivisible goods among agents with additive valuations, using the popular fairness notion of maximin share (MMS). Since MMS allocations do not always exist, a series of works provided existence and algorithms for approximate MMS allocations. The Garg-Taki algorithm gives the current best approximation factor of . Most of these results are based on complicated analyses, especially those providing better than factor. Moreover, since no tight example is known of the Garg-Taki algorithm, it is unclear if this is the best factor of this approach. In this paper, we significantly simplify the analysis of this algorithm and also improve the existence guarantee to a factor of . For small , this provides a noticeable improvement. Furthermore, we present a tight example of this algorithm, showing that this may be the best factor one can hope for with the current techniques.
arxiv.org
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