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Applying Queueing Theory for the Optimization of a Banking Model

Kevin W. G. Cowdrey,
Jaco de Lange,
Reza Malekian,
Johan Wanneburg,
Arun Cyril Jose,

Abstract


The purpose of this paper is to investigate waiting times at banking firms to design a system to optimise the overall banking experience. Queueing analysis and queuing theory will be investigated and applied in order to improve customer experience whilst maximising profits. Different queueing strategies will be implemented using waiting time as a performance measurement. In order to find the most efficient solution the following queuing methods will be investigated: First in First out (FIFO), Last in First out (LIFO), Shortest Job First (SJF), Longest Job First (LJF), most profitable job first and priority queues. After investigation, design and simulation, queuing strategies will be implemented on a real world banking scenario whilst introducing banking traffic at different times of the day as well as disturbances such as tellers going offline. A practical design includes a Field Programmable Gate Array (FPGA) in order to simulate the banking scenario. The FPGA approach will provide a mobile solution for the optimization of queueing in a banking firm which could later be implemented in a banking firm for a better banking experience. Based on results obtained, the SJF method produces the best customer satisfaction, whilst most profitable job first queues maximizes profits.

Citation Format:
Kevin W. G. Cowdrey, Jaco de Lange, Reza Malekian, Johan Wanneburg, Arun Cyril Jose, "Applying Queueing Theory for the Optimization of a Banking Model," Journal of Internet Technology, vol. 19, no. 2 , pp. 381-389, Mar. 2018.

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Published by Executive Committee, Taiwan Academic Network, Ministry of Education, Taipei, Taiwan, R.O.C
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