Explore how to reduce waiting and variance in complex service networks.
This book analyzes scheduling choices in multiclass queueing systems and shows how to balance efficiency with fairness across customer types.
It introduces a practical surrogate for measuring fairness: the sum of squared differences between the mean sojourn times of different customer types. The work compares three network setups and uses a Brownian network model to approximate optimal control policies under heavy loading. It also contrasts common rules like FCFS with policy approaches designed to improve both mean performance and variability, supported by simulation studies.
- Learn how surrogate variance is defined and why it matters for overall system performance
- See how three network architectures are analyzed and how scheduling decisions are made
- Discover how FCFS performs and where alternative, workload‑driven policies can help
- Understand the Brownian control framework and its role in designing practical policies
Ideal for readers of operations research, applied probability, and manufacturing systems who want concrete methods for reducing both average wait and variability.