Open AccessBank Queuing Optimization Based on Markov Process
Author(s) -
Yuan He,
Haoxuan Li
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1616/1/012055
Subject(s) - queueing theory , markov chain , computer science , process (computing) , markov process , mathematical optimization , computer network , mathematics , machine learning , statistics , operating system
Queuing optimization is a troubling problem in the field of operations research and it is difficult to solve completely due to the complexity and uncertainty of the queuing environment. Among them, bank queuing optimization is the most widespread and representative in the queuing theory. This article focuses on using customer arrival and service of cashiers to establish birth-death process and its transfer rate matrix. By introducing service intensity and customer satisfaction index, it is concluded that the optimal number of open cashiers in different time period can be calculated and predicted.