To save the opportunity cost also, this study used a qualitative approach with quantitative analysis of the queuing system. Customer perception means the experience of customers in a system which results in the customerвЂ™s satisfaction. Hence the system has the opportunity to save this cost by involving customerвЂ™s perception in the designing phase of the system that what actually customerвЂ™s need in the system. I used the term вЂњopportunity costвЂќ because in the system, there is no need for zero waiting time in the system. By studying literature such as, we found that customerвЂ™s satisfaction is not only based on minimum waiting time but also involved perception of waiting time in the system.

For waiting time minimization, extra resources are required in the system which causes an addition of cost to the system. By quantitative method the system is facing the issue of opportunity cost. The use of queuing analysis and simulation has been widely discussed in literature by. Also by using simulation, it permits you to experiment your designs without requiring acquisition of resources. Queuing model is very applicable in making decisions about the level of staff, building layout, resource allocation, and new policies implementation. To optimize the system and decrease the extra cost of counters, queuing theory and simulation has been used in quantitative analysis of the bank. Most of the time having many counters significantly increases the cost of the system.

To provide quick service in a bank system, many counters are provided to customers. INTRODUCTION Many service systems including banks are trying to provide quick service to customers. Keywords-queuing theory simulation customer perception ssub-optimization. The resulting design has a fewer number of service representatives, higher utilization and a waiting time within the limit of the customerвЂ™s expected time. вЂA quantitative analysis and simulation was conducted and sub-optimized the system. Finally, building and validation of a computer simulation model of a bank queuing system was conducted by using POM-QM software. Next, we suggested qualitative approach in the designing of queuing system of the bank. We find out that the utilization of the system was very ineffective. Second, we analyzed the inter arrival time and service time by using the quantitative method and forecast the improvement in the system. Arrival time of customers, service time, and the waiting time customers are willing to wait are all included in the data collection. First, observation of the system was conducted and recorded using the existing operations system used by the bank. By using the qualitative approach, M/M/s queuing model and discrete event simulation, the staff was suboptimized. Due to extra and imbalanced staff, the system was idle most of the time. School of computer and communication engineering Department of computer science and technology University of science and technology Beijing 100083 Beijing, PR ChinaДepartment of Industrial Engineering Sabanci University Istanbul Orhanli, 34956, Istanbul Turkey ДЄbstract-This paper is a study of staff issues at the bank, ICBC China.

Sub-optimization of Bank Queuing System by Qualitative and Quantitative Analysis Azmat UllahДepartment of management science and engineering Dongling School of economics and management University of science and technology Beijing 100083 Beijing, PR China Дepartment of Management Science and Engineering Dongling School of economics and management University of science and technology Beijing 100083 Beijing, PR China

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