Customer Arrival Event Processing on Computer Simulation for Discrete Event System

Article Preview

Abstract:

Discrete event systems are widely used in the production and life, it is difficult to use conventional differential equations, differential equations, and other models to describe, the theoretical analysis method is difficult to obtain analytical solutions, computer simulation techniques to solve these problems provides an effective means. Arrival event is a typical discrete system event; on arrival event handling is always one of the difficulties of computer simulation, in this paper, banking customer arrival system as an example to study. For banks queuing system, customers arrive to obey the parameter of Poisson distribution is, the probability mass function through the distribution curves and cumulative distribution function curves to study the distribution of customer arrival; construction of single-queue multi-server system of customer arrival event subroutine flow chart, and processing steps will be described. Content of this study, it is suitable for the developed area bank to adopt "number ticket machine" approach to service.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

2133-2136

Citation:

Online since:

February 2014

Export:

Price:

* - Corresponding Author

[1] Moamar Sayed-Mouchaweh, Decentralized Fault Free Model Approach for Fault Detection and Isolation of Discrete Event Systems, European Journal of Control, vol. 18, no. 1, pp.82-93, (2012).

DOI: 10.3166/ejc.18.82-93

Google Scholar

[2] R. Y. Liu, H. L. Ren, Z. M. Li Foundation of computer simulation technology, Publishing House of electronics industry, (2011).

Google Scholar

[3] SouthwestJiaotongUniversity, Poissondistribution, http: /wenku. baidu. com/view/b39b7941a89 56bec0975e363. html, 2013-10-30.

Google Scholar

[4] C. F. Xu, Poisson distribution and Poisson flow, Silicon Valley, vol. 9, no. 4, p.11, (2010).

Google Scholar

[5] C. Su, Probability theory, Science Press, (2004).

Google Scholar

[6] Sheldon M. Ross. A First Course in Probability[M]. Prentice Hall, (2010).

Google Scholar

[7] Z. X. Yang, Computer simulation and its application, China Railway Publishing House, (1999).

Google Scholar

[8] A. Azadeh, Z.S. Faiz, S.M. Asadzadeh, R. Tavakkoli-Moghaddam, An integrated artificial neural network-computer simulation for optimization of complex tandem queue systems, Mathematics and Computers in Simulation, vol. 82, no. 4, pp.666-678, (2011).

DOI: 10.1016/j.matcom.2011.06.009

Google Scholar