Analyzing,Optimizing The Customer Queue Of Longhua Subbranch Of The A Bank

On the basis of summarizing queuing theory,simulation theory and queuing system optimization literature,this paper analyzes the running status of longhua subbranch queuing system and finds the feasible system optimization method.The core parameters of the longhua subbranch queuing service system are analyzed in depth,and the actual situation of the queuing system is analyzed.The realistic queuing system is simulated by simulation method,and the window setting strategy is adjusted to carry out the actual optimization analysis of the counter window.Considering some management strategies of the queuing system,and analyzing corporate customers,VIP customers and ordinary customers in the actual queuing system.As a result,different customers' arrival rates comply with different experience distributions: individual customers' arrival in the normal distribution,VIP customers' arrival in compliance with the beta distribution,the companies' arrivals obey the Weibull distribution,correspondingly,the customers' arrival interval follows the beta distribution,Gamma distribution and Weibull distribution.The customers arrive at double-peak time.Customers prefer to coming in business days other than weekend,so as the loss rate.Another important parameter in the queuing system is to the service time to the customer.According to the service strategy,the counter is divided into three categories,for a single type of customer counter,for two types of customer counters and three types of customer counters,three types of counter external services Time also follows a different experience distribution.Simulation modeling simulates the bank queuing system and makes an effective optimization.The simulation model works well.Old counter opening strategy open a number of counters one day,the different counters provide services for different customer groups.through the open strategy,all customers are at full coverage.The new open strategy to reduce the number of VIP counters appropriately reduces the flow of high cabinet customers,increases the number of customers to the mixed service counters.The simulation results of the new strategy show that the average waiting time of customers in the queuing system is greatly reduced.