English(EN) Lag: A Mean-Field Optimal Policy for Online Assignment with Reusable Resources

新的“Lag”策略为在线任务分配提供最优解决方案

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-15 04:00

研究人员开发了一种名为Lag的新均场最优策略，用于具有可复用资源的在线任务分配。该问题与同行评审分配、呼叫路由和拼车匹配等各种应用相关。所提出的策略源自占用度量线性规划（OCC-LP），在特定缩放机制下被证明是渐近最优的，并且在同行评审和呼叫中心数据评估中显著优于贪婪分配方案。 AI

影响为优化各种在线分配问题中的资源分配引入了新颖的策略。

排序理由该集群包含一篇详细介绍新算法及其评估的学术论文。[lever_c_demoted from research: ic=1 ai=0.7]

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arXiv cs.LG TIER_1 English(EN) · Keerthana Gurushankar · 2026-10-15 04:00

Lag: 一种具有可复用资源的在线分配的均场最优策略

arXiv:2610.19038v1 Announce Type: new Abstract: We study online task assignment with reusable resources. This problem arises in peer reviewer assignment, skill-based call routing, rideshare matching, emergency dispatch, and crowdsourcing: Tasks arrive according to a geometric pro…