Applying Empirical Bayesian Estimation in the Optimal Decision of Server-Dependent Queue Under the (M,Q) Policy

• Main Authors: Shih-Ting Yang, 楊士霆
• Other Authors: Yun-Cheng Huang
• Format: Others
• Language: zh-TW
• Published: 2003
• Online Access: http://ndltd.ncl.edu.tw/handle/50332661300513335725

碩士 === 國立屏東科技大學 === 工業管理系 === 91 === The queueing system that the number of servers is changed depends on the length of queue. It is different from the traditional one because the number of servers is decided by the number of customers in the waiting line . In order to make the service and arrival rates close to reality, this study estimates the traffic intensity (i.e. the parameter of queueing system, ρ) by the Empirical Bayesian estimation method. In addition, we consider those parameters of cost in the research. Base on them, we can find the optimal solution M and Q (i.e. M , Q Policy)to maximize the total expected profit. According to it, we can make the decision when to turn on and turn off the second server. After deriving the model, the numerical analysis was performed and six conclusions are drawn for future studies and applications.