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學術報告:Equilibrium Strategies in M/M/1 Priority Queues with Balking

報告時間201865日(周二)9:30

報告地點:河北工業大學西教五416室(理學院)

主辦單位:河北工業大學理學院河北工業大學數學研究院

報告題目Equilibrium Strategies in M/M/1 Priority Queues with Balking

報告嘉賓:王金亭

 

嘉賓簡介

 

王金亭,男,博士生導師,我校校友,教育部新世紀優秀人才計劃獲得者,北京交通大學運籌學研究所副所長、理學院數學系支部書記、副主任。2000年在中國科學院應用數學所獲博士學位,專業為運籌學與控制論。研究領域為隨機運籌優化、應用概率統計等?,F任中國運籌學會可靠性分會理事長、中國運籌學會隨機服務與運作管理分會副理事長、中國運籌學會理事、北京運籌學會副理事長。2006年獲得教育部霍英東教育基金會第十屆高等院校青年教師獎,2011年入選教育部新世紀優秀人才支持計劃。近五年在Production and Operations Management、IEEE Transactions on Vehicular Technology、Naval Research Logistics、Journal of the Operational Research Society、Reliability Engineering and System Safety、European Journal of Operational Research等領域內知名期刊上發表SCI檢索論文50余篇,出版著作《排隊博弈論基礎》(20166月,科學出版社)。

報告摘要

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.