Evaluating the Bank Queuing Systems by Fuzzy Logic

Halil Kilif, I. Ozkan
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Abstract

Various models are used in the banking system to organize the queue structure of customers' banking transactions. The average waiting time for a customer in the queue generally varies depending on whether bank customer or not and the customer score it has. Different uncertain parameters are used to determine the individual queue group and average waiting time in bank queuing systems. This paper proposes a fuzzy logic-based approach in bank queuing systems. In this study, individual bank queue group and average waiting times are determined according to the number of waiting customers, customer score and credit score parameters. In addition, identification number is a determining factor for the priority of transactions in bank queuing systems. People who are not customers of the bank often have longer waiting times. As a new approach to the working structure of bank queuing systems, this study also suggests that non-bank customers should be given priority sequence numbers according to their credit scores.
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用模糊逻辑评价银行排队系统
银行系统使用各种模型来组织客户银行交易的队列结构。排队中客户的平均等待时间通常取决于是否为银行客户及其客户得分。在银行排队系统中,使用不同的不确定参数来确定单个队列组和平均等待时间。本文提出了一种基于模糊逻辑的银行排队系统求解方法。在本研究中,根据等待客户数量、客户评分和信用评分参数确定各银行的排队群体和平均等待时间。此外,在银行排队系统中,身份证号是决定交易优先级的一个因素。不是银行客户的人通常需要更长的等待时间。作为银行排队系统工作结构的新方法,本研究还建议非银行客户应根据其信用评分给予优先序列号。
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