对抗制
计算机科学
运筹学
帧(网络)
资源配置
微观经济学
业务
经济
计算机网络
人工智能
数学
作者
Gerdus Benadè,Aleksandr M. Kazachkov,Ariel D. Procaccia,Alexandros Psomas,David Zeng
出处
期刊:Operations Research
[Institute for Operations Research and the Management Sciences]
日期:2023-11-03
标识
DOI:10.1287/opre.2022.0332
摘要
Trade-Offs in Dynamic Allocation Problems Food rescue organizations often receive donations to allocate to food pantries or families. Donations are unpredictable, and goods are often perishable; as a result, allocations have to be made within a short time frame after arrival without knowledge of future arrivals. It is important that donations go to organizations that are able to use them; at the same time, organizations that serve different communities should be treated equitably. In “Fair and Efficient Online Allocations,” Benadè, Kazachkov, Procaccia, Psomas, and Zeng study fairness-efficiency trade-offs in such online allocation problems. Against adversarial arrivals, no algorithm can provide nontrivial guarantees for both these objectives simultaneously. When item values are drawn from (potentially correlated) distributions, there is no trade-off, and a simultaneously fair and efficient algorithm is presented.
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