When does admission control reduce congestion? A stochastic ordering approach
Admission control is a widely used mechanism for regulating congestion in stochastic service systems, where restricting arrivals is expected to reduce workload and improve performance. In many settings, however, customers make decisions based on the observed system state, creating a feedback loop between control actions and future arrivals. This raises a fundamental question: does admission control necessarily reduce congestion under state-dependent behavior? We address this question using stochastic ordering of workload processes. We show that admission control may fail to reduce congestion due to endogenous feedback effects, and construct explicit counterexamples illustrating this phenomenon. We then identify a general condition under which admission control is effective over the initial busy period. In particular, independence between customers' types and service requirements eliminates the adverse feedback mechanism and restores stochastic dominance. These results highlight fundamental limitations of admission control and the importance of accounting for behavioral responses in the design of stochastic service systems.