fair-mab-balancing

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基于Fair-MAB算法确保工人获得公平的任务分配机会，避免高效工人被过度使用

j4xie

By j4xie schedule Updated 2/20/2026

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name: fair-mab-balancing displayName: 公平性均衡调度 description: 基于Fair-MAB算法确保工人获得公平的任务分配机会，避免高效工人被过度使用 version: 1.0.0 triggers: - "公平分配" - "均衡调度" - "轮换" - "公平性" tools: - FairMABService - WorkerAllocationFeedbackRepository contextNeeded: - factoryId - workerHistory parameters: fairnessRatio: 0.8 explorationBonus: 0.1 virtualQueueDecay: 0.95 requiredPermission: "scheduling:fairness:execute" category: "scheduling" priority: 60

功能说明

基于学术论文 "Fair Learning for Combinatorial MAB" 实现

核心公式

Score(w,t) = LinUCB(w,t) + α × FairnessBonus(w) + β × VirtualQueue(w)

参数说明

fairnessRatio: 目标公平比例，每个工人至少获得此比例的任务
explorationBonus: 探索加成，鼓励尝试不常分配的工人
virtualQueueDecay: 虚拟队列衰减率

Install via CLI

npx skills add https://github.com/j4xie/my-prototype-logistics --skill fair-mab-balancing

Repository Details

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Occupations

Operations Research Analysts 152031

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