Dynamic Assignment of Objects to Queuing Agents
研究了将对象动态分配给固定规模等待列表中的代理，分析了概率排队规则、惩罚机制和信息披露的最优设计，发现不同价值类型下代理偏好和浪费情况不同。
We analyze the dynamic assignment of objects to agents organized in a constant size waiting list. Applications include the assignment of social housing and organs for transplants. We analyze the optimal design of probabilistic queuing disciplines, punishment schemes, and information release. With private values, all agents prefer first-come first-served to the lottery, but waste is lower at the lottery. With common values, all agents prefer first-come first-served to any other mechanism, and waste is minimized at the lottery. Punishment schemes accelerate turnover in the queue and information release increases the value of agents at the top of the waiting list.