Pointwise Stationary Fluid Models for Stochastic Processing Networks

• 成果类型: Article
• 署名作者: Bassamboo, Achal; Harrison, J. Michael; Zeevi, Assaf
• 署名单位: Northwestern University; Stanford University; Columbia University
• 刊物名称: M&SOM-MANUFACTURING & SERVICE OPERATIONS MANAGEMENT
• ISSN/ISSBN: 1523-4614
• DOI: 10.1287/msom.1070.0195
• 发表日期: 2009
• 页码: 70-89
• 关键词: Admission control; dynamic routing; doubly stochastic arrivals; approximation; pointwise stationary; fluid models; abandonments; stochastic networks

摘要

Generalizing earlier work on staffing and routing in telephone call centers, we consider a processing network model with large server pools and doubly stochastic input flows. In this model the processing of a job may involve several distinct operations. Alternative processing modes are also allowed. Given a finite planning horizon, attention is focused on the two-level problem of capacity choice and dynamic system control. A pointwise stationary fluid model (PSFM) is used to approximate system dynamics, which allows development of practical policies with a manageable computational burden. Earlier work in more restrictive settings suggests that our method is asymptotically optimal in a parameter regime of practical interest, but this paper contains no formal limit theory. Rather, it develops a PSFM calculus that is broadly accessible, with an emphasis on modeling and practical computation.