The IUFP Algorithm for Generating Simulation Heart

Document Type : Research Article

Authors

1 Corresponding Author, E. Shadkam, PhD student, Department of Industrial Engineering, Isfahan University of Technology, Isfahan, Iran

2 A. Aghaie, Professor, Department of Industrial Engineering, K.N. Toosi University of Technology, Tehran, Iran (aaghaie@kntu.ac.ir

Abstract

In all systems simulation, random variates are considered as a main factor and based of simulation heart. Actually, randomization is inducted by random variates in the simulation. Due to the importance of such a problem, a new method for generation of random variates from continuous distributions is presented in this paper. The proposed algorithm, called uniform fractional part (UFP) is simpler and more efficient compared with other methods of random variates generation. Despite useful consequences, this algorithm has several shortcomings such as 1) being approximate, 2) not accessibility of the inverse of cumulative density function (CDF) for all distributions in order to determine the cut-off points and 3) truncating the tails of infinite distributions, which all of the aforementioned shortcomings reduce the precision and speed of the algorithm. The main goal of this research is proposing the improved version of this algorithm (IUFP) through recognizing its deficiencies. 

Keywords

References

[1]     Banks, J.; Handbook of simulation principle, methodology, advances, applications and practice, 3nd Edition, New York: John Wiley & Sons, 1998.
[2]     Hung, Y. C.; Balakrishnan, N.; Cheng C. W.; “Evaluation of algorithms for generating Dirichlet random vectors”, Journal of Statistical Computation and Simulation, 2010.
[3]     Banks, J.; Carson, J.S.; Nelson, B.L.; Nicol, D.M.; Discrete-event system simulation, 1nd Edition, Upper Saddle River: Pear-son Prentice Hall, 2005.
[4]     Ormann, W.; Erflinger, G.; “The transformed rejection method for generating random variables, an alternative to the ratio of uniforms method” Communications in Statistics - Simulation and Computation, vol. 23, 3, p.p. 847 – 860, 1994.
[5]     Mahlooji, H.; Jahromi, A.E.; Mehrizi, H.A.; Izady,N.; “Uniform Fractional Part: A simple fast method for generating continuous random variates”, Scientia Iranica, vol. 15,5, p.p. 613-622, 2008.
[6]     Jones, M. C A.; Lunn, D.; “Transformations and random variate generation: generalised ratio-of-uniforms methods”, Journal of Statistical Computation and Simulation, vol. 55, 1, p.p. 49-55, 1996.
[7]     Cheng, R. C. H.; Feast, G. M.; “Some simple gamma variate generators”, appl statist, vol. 28,3, p.p. 290-295, 1979.
[8]     Morgan, B.J.T.; Elements of simulation, 1ed Edition, London: Chapman and Hall, 1984.
[9]     Mahlooji, H.; Izady, N.; “Developing a Wide Easy-to-Generate Class of Bivariate Copulas”, Communications in Statistics -Theory and Methods, vol. 37, p.p. 1919–1929, 2008. 
[10]  Mahlooji, H.; Mehrizi, H.A.; Farzan, A.; “A fast method for generating continuous order statics based on uniform fractional part”, Proc. 35th International Conference on Computers and Industrial Engineering, p.p. 1355-1360, 2004.
Mahlooji, H.; Mehrizi, H.; Sedghi, N.; “An efficient, fast and portable random number generator”, Proc.35th International 

Files

Share

How to cite

Statistics