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New 'Lag' policy offers optimal solution for online task assignment

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a new mean-field optimal policy called Lag for online task assignment with reusable resources. This problem is relevant in various applications such as peer reviewer assignment, call routing, and rideshare matching. The proposed policy, derived from an occupancy-measure linear program (OCC-LP), is shown to be asymptotically optimal in a specific scaling regime and significantly outperforms the greedy assignment scheme in evaluations on peer review and call center data. AI

IMPACT Introduces a novel policy for optimizing resource allocation in various online assignment problems.

RANK_REASON The cluster contains an academic paper detailing a new algorithm and its evaluation. [lever_c_demoted from research: ic=1 ai=0.7]

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New 'Lag' policy offers optimal solution for online task assignment

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The cluster contains an academic paper detailing a new algorithm and its evaluation. [lever_c_demoted from research: ic=1 ai=0.7]
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COVERAGE [1]

  1. arXiv cs.LG TIER_1 English(EN) · Keerthana Gurushankar ·

    Lag: A Mean-Field Optimal Policy for Online Assignment with Reusable Resources

    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…

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