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新算法增强了带可移除物品的在线背包问题

本文介绍了在线无权重背包问题的新算法,重点关注已接受物品可被移除的场景。研究通过结合物品大小界限知识和重新插入先前拒绝物品的能力,来探索竞争比的改进。此外,本文还提出了自适应在线算法,这些算法在不需要预先了解物品大小界限的情况下,也能达到可比的性能。 AI

影响 这项研究推动了理论计算机科学的发展,可能影响未来AI系统中使用的优化算法。

排序理由 该集群包含一篇在arXiv上发表的学术论文,详细介绍了针对特定计算问题的新算法。[lever_c_demoted from research: ic=1 ai=0.4]

在 arXiv cs.CL 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

新算法增强了带可移除物品的在线背包问题

本文如何被排名

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Tool
该集群包含一篇在arXiv上发表的学术论文,详细介绍了针对特定计算问题的新算法。[lever_c_demoted from research: ic=1 ai=0.4]
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Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
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paper, other
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Standard
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Fresh story with cross-source coverage still developing. Ranking may shift as more sources report.

完整方法见我们的编辑标准。

报道来源 [1]

  1. arXiv cs.CL TIER_1 English(EN) · Dimitris Fotakis, Laurent Gourv\`es, Aris Pagourtzis, Panagiotis Patsilinakos ·

    利用追索权和大小界限解决带可移除物品的在线背包问题

    arXiv:2610.40290v2 Announce Type: replace-cross Abstract: In the online unweighted knapsack problem, items arrive sequentially and must be accepted or rejected immediately for a bounded-capacity knapsack, aiming to maximize the total size of accepted items. When decisions are irr…