Publisher's Synopsis
This technical work presents a distributional form of Little's Law, a foundational principle in queueing theory and operations management. The research, originating from the Sloan School of Management, delves into the statistical properties of queueing systems, providing a rigorous mathematical treatment suitable for advanced students and researchers in the fields of operations research, applied probability, and industrial engineering. The authors, Julian Keilson and L. D. Servi, explore the relationship between the number of customers in a system, their arrival rate, and their average time spent in the system, extending the classical Little's Law to encompass distributional aspects. This analysis offers valuable insights for optimizing system performance and predicting system behavior under various stochastic conditions. This is a valuable resource for those seeking a deeper understanding of the mathematical underpinnings of queueing theory.
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