Predictive Business Forecasting using Queue Simulation

Abstract: Queues are not merely an object to study. Queues are real world problems faced by customers at a busi-ness station that kill their valuable time. This results in decreased customer interest and the progress trends towards a loss. This is particularly frightful with smaller investments, where a single loss may permanently eliminate the business. It is not enough to know how queue behaves, but we are also required to know how to eliminate queues or at least how to reduce them to a manageable size. It is possible to reduce the queuing delay by changing the service mechanism. This involves increasing the rate at which customers are being served. Queues grow when customers happen to arrive at a faster rate than they are being served. This type of service dependent queues may be eliminated or at least reduced by developing a demand responsive service strategy that reduces the service time variation. Practical business transactions are too complex to be studied analytically. Besides, analysis using the collective practical data is hugely expensive and prohibitively time consuming that may affect the investment in-centives. In this paper, a queuing model to simulate a small commercial establishment has been proposed, and a C++ program, which is founded on the model, is implemented. Simulation data plots are presented and the data tables are analyzed to make predictive forecasting over the significant transaction factors. Mathematical analysis fundamental to the proposed model is also incorporated, so that the model may be extended to a multitude of other similar applications in future