Academic Commons

Theses Doctoral

Staffing and Scheduling to Differentiate Service in Many-Server Service Systems

Sun, Xu

This dissertation contributes to the study of a queueing system with a single pool of multiple homogeneous servers to which multiple classes of customers arrive in independent streams. The objective is to devise appropriate staffing and scheduling policies to achieve specified class-dependent service levels expressed in terms of tail probability of delays. Here staffing and scheduling are concerned with specifying a time-varying number of servers and assigning newly idle servers to a waiting customer from one of K classes, respectively. For this purpose, we propose new staffing-and-scheduling solutions under the critically-loaded and overloaded regimes. In both cases, the proposed solutions are both time dependent (coping with the time variability in the arrival pattern) and state dependent (capturing the stochastic variability in service and arrival times). We prove heavy-traffic limit theorems to substantiate the effectiveness of our proposed staffing and scheduling policies. We also conduct computer simulation experiments to provide engineering confirmation and practical insight.

Files

  • thumnail for Sun_columbia_0054D_15168.pdf Sun_columbia_0054D_15168.pdf application/pdf 1.37 MB Download File

More About This Work

Academic Units
Industrial Engineering and Operations Research
Thesis Advisors
Whitt, Ward
Degree
Ph.D., Columbia University
Published Here
April 24, 2019
Academic Commons provides global access to research and scholarship produced at Columbia University, Barnard College, Teachers College, Union Theological Seminary and Jewish Theological Seminary. Academic Commons is managed by the Columbia University Libraries.