An FPTAS for 7/9-Approximation to Maximin Share Allocations
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arXiv
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| Format: | Preprint |
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2025
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| _version_ | 1866909907974881280 |
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| author | Huang, Xin Zhou, Shengwei |
| author_facet | Huang, Xin Zhou, Shengwei |
| contents | We present a new algorithm that achieves a $\frac{7}{9}$-approximation for the maximin share (MMS) allocation of indivisible goods under additive valuations, improving the current best ratio of $\frac{10}{13}$ (Heidari et al., SODA 2026). Building on a new analytical framework, we further obtain an FPTAS that achieves a $\frac{7}{9}-\varepsilon$ approximation in $\tfrac{1}{\varepsilon} \cdot \mathrm{poly}(n,m)$ time. Compared with prior work (Heidari et al., SODA 2026), our algorithm is substantially simpler. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2511_13056 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | An FPTAS for 7/9-Approximation to Maximin Share Allocations Huang, Xin Zhou, Shengwei Computer Science and Game Theory Data Structures and Algorithms We present a new algorithm that achieves a $\frac{7}{9}$-approximation for the maximin share (MMS) allocation of indivisible goods under additive valuations, improving the current best ratio of $\frac{10}{13}$ (Heidari et al., SODA 2026). Building on a new analytical framework, we further obtain an FPTAS that achieves a $\frac{7}{9}-\varepsilon$ approximation in $\tfrac{1}{\varepsilon} \cdot \mathrm{poly}(n,m)$ time. Compared with prior work (Heidari et al., SODA 2026), our algorithm is substantially simpler. |
| title | An FPTAS for 7/9-Approximation to Maximin Share Allocations |
| topic | Computer Science and Game Theory Data Structures and Algorithms |
| url | https://arxiv.org/abs/2511.13056 |