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学术报告:Equilibrium Strategies in M/M/1 Priority Queues with Balking

报告时间201865日(周二)9:30

报告地点:河北工业大学西教五416室(理学院)

主办单位:河北工业大学理学院河北工业大学数学研究院

报告题目Equilibrium Strategies in M/M/1 Priority Queues with Balking

报告嘉宾:王金亭

 

嘉宾简介

 

王金亭,男,博士生导师,我校校友,教育部新世纪优秀人才计划获得者,北京交通大学运筹学研究所副所长、理学院数学系支部书记、副主任。2000年在中国科学院应用数学所获博士学位,专业为运筹学与控制论。研究领域为随机运筹优化、应用概率统计等。现任中国运筹学会可靠性分会理事长、中国运筹学会随机服务与运作管理分会副理事长、中国运筹学会理事、北京运筹学会副理事长。2006年获得教育部霍英东教育基金会第十届高等院校青年教师奖,2011年入选教育部新世纪优秀人才支持计划。近五年在Production and Operations ManagementIEEE Transactions on Vehicular TechnologyNaval Research LogisticsJournal of the Operational Research SocietyReliability Engineering and System SafetyEuropean Journal of Operational Research等领域内知名期刊上发表SCI检索论文50余篇,出版著作《排队博弈论基础》(20166月,科学出版社)。

报告摘要

We consider an M/M/1 queueing system with a pay-for-priority option, and study customers' joint decisions between joining/balking and pay-for-priority. The equilibrium strategies are thus two-dimensional. First, we fully characterize the equilibrium structure and identify the Pareto-dominant strategies of such a game analytically, under both the observable and unobservable settings. Interestingly, the equilibrium structure, the system throughput, and the service provider's optimal price for priority premium can all be non-monotone in the service reward, which departs from the existing models of priority queues without balking. In particular, we find that an increase in service reward can actually hurt the firm's revenue (everything else being equal). Second, we compare the server's revenue between the observable and the unobservable settings. We find that the service provider is better off with the observable setting when the system load is either low or high, but benefits more from the unobservable setting when the system load is medium. The fact that the optimal setting switches twice as the system load increases, is rather interesting; we explain the intuitions behind it in this paper. Finally, we demonstrate the implications of these findings by applying our model framework to Papa John's Pizza, based on publicly available information. Our analysis suggests that Papa John's could benefit from providing customers with wait information while slightly decreasing its fee for Papa Priority.

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