2023/02/22 by Shuangning Li, Ramesh Johari, Li, Shuangning +4 · 5 citations
Business, Management and Accounting · Engineering · #Advanced Queuing Theory Analysis #FOS: Computer and information sciences #FOS: Electrical engineering #FOS: Mathematics #Methodology (stat.ME) #Optimization and Control (math.OC) #Smart Grid Energy Management #Systems and Control (eess.SY) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2302.12093
openalex publication_date 2023/02/22 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01
We study randomized experiments in a service system when stochastic congestion can arise from temporarily limited supply or excess demand. Such congestion gives rise to cross-unit interference between the waiting customers, and analytic strategies that do not account for this interference may be biased. In current practice, one of the most widely used ways to address stochastic congestion is to use switchback experiments that alternatively turn a target intervention on and off for the whole system. We find, however, that under a queueing model for stochastic congestion, the standard way of analyzing switchbacks is inefficient, and that estimators that leverage the queueing model can be materially more accurate. Additionally, we show how the queueing model enables estimation of total policy gradients from unit-level randomized experiments, thus giving practitioners an alternative experimental approach they can use without needing to pre-commit to a fixed switchback length before data collection.