Refined mean‐field approximation for discrete‐time queueing networks with blocking
针对离散时间带阻塞的排队网络，提出一种精细化平均场近似方法，显式量化了收敛速度，在小规模系统中显著提升了性能预测精度，有助于实际决策支持。
Abstract We study a discrete‐time queueing network with blocking that is primarily motivated by outpatient network management. To tackle the curse of dimensionality in performance analysis, we develop a refined mean‐field approximation that deals with changing population size, a nonconventional feature that makes the analysis challenging within the existing literature. We explicitly quantify the convergence rate for this approximation as with being the system size. Not only is this convergence better than the convergence proven in prior work, but our approximation shows a significant improvement in performance prediction accuracy when the system size is small, compared to the conventional (unrefined) mean‐field approximation. This accuracy makes our approximation appealing to support decision‐making in practice.