2023.5.26 10:00 N613

This paper considers a tandem queueing system, in which stage 1 has one station serving multiple classes of arriving customers differing in their service requirements and related delay costs, and stage 2 has multiple parallel stations, each of which provides one type of service. Each station has many statistically identical servers. The objective is to design a joint capacity allocation between the stages/stations and scheduling rule of different classes of customers to minimize the long-run average cost. Using fluid approximation, we convert the stochastic problem into a fluid optimization problem and develop a procedure to solve it. Based on the solution to the fluid optimization problem, we propose a simple and easy-to-implement capacity allocation and scheduling policy, and establish its asymptotic optimality for the stochastic system. The policy has explicit index-based forms for two special system structures: the many-to-one and one-to-many systems. We further propose a grouping and pooling strategy to streamline the operations of the service system. Finally, we conduct numerical experiments to validate the accuracy of the fluid approximation, and quantify the effect of grouping and pooling based on fluid optimal solution.

黄军飞博士毕业于新加坡国立大学, 现为香港中文大学商学院副教授。他的 研究兴趣包括排队系统的渐近分析和最优控制及相关理论在生产、服务系统中的应用。他获 得了优秀青年科学基金（港澳），香港中文大学青年学者研究成就奖，MSOM Service Management SIG Best Paper Award（MSOM 协会）及 Uriel G. Rothblum Prize for Excellent in Operations Work Research （以色列运筹学会）等科研奖项。