The research objective of this BRIGE award is to investigate the trade-off between service capacity and quality of service within the modeling framework of queueing networks. Service capacity will be measured by staffing levels, while quality of service will be measured by expected customer delays. New methodology will be developed in the context of stochastic processing networks, which will be combined with numerical optimization techniques. Three application areas will provide a testbed for the evaluation of the proposed methods: telephone call centers, health care systems, and workforce management.
If successful, the results of this research will help improve the efficiency of business processes in some of today's competitive service environments. Since the staffing levels of service personnel constitute a significant portion of the costs involved in many large-scale service systems, systematic allocation of service capacity is particularly relevant in this context. Standard software for process management and optimization uses simulation techniques to allocate service capacity, and therefore essentially only computationally expensive techniques are used in practice. The proposed research agenda identifies and exploits mathematical models that can be used for allocating service capacity in combination with simulation methods, which will potentially lead to more efficient capacity allocation rules for service systems. The research project will be integrated with a comprehensive plan to attract high school students from underrepresented groups to careers in engineering. A key aspect of this plan is the development of a computer program in which students are challenged to manage queues in an amusement park.
