ACM Home Page
Please provide us with feedback. Feedback
Software for uniform random number generation: distinguishing the good and the bad
Full text PdfPdf (176 KB)
Source Winter Simulation Conference archive
Proceedings of the 33nd conference on Winter simulation table of contents
Arlington, Virginia
TUTORIAL SESSION: Advanced tutorials table of contents
Pages: 95 - 105  
Year of Publication: 2001
ISBN:0-7803-7309-X
Author
Pierre L'Ecuyer  Université de Montréal, C.P. 6128, Succ. Centre-Ville, Montréal, H3C 3J7, CANADA
Sponsors
INFORMS/CS : Institute for Operations Research and the Management Sciences/College on Simulation
IEEE/SMCS : Institute of Electrical and Electronics Engineers/Systems, Man, and Cybernetics Society
NIST : National Institute of Standards and Technology
ACM: Association for Computing Machinery
SCS : The Society for Computer Simulation International
SIGSIM: ACM Special Interest Group on Simulation and Modeling
IIE : Institute of Industrial Engineers
IEEE/CS : Institute of Electrical and Electronics Engineers/Computer Society
ASA : American Statistical Association
Publisher
IEEE Computer Society  Washington, DC, USA
Bibliometrics
Downloads (6 Weeks): 14,   Downloads (12 Months): 104,   Citation Count: 8
Additional Information:

abstract   references   cited by   index terms   collaborative colleagues   peer to peer  

Tools and Actions: Review this Article  

ABSTRACT

The requirements, design principles, and statistical testing approaches of uniform random number generators for simulation are briefly surveyed. An object-oriented random number package where random number streams can be created at will, and with convenient tools for manipulating the streams, is presented. A version of this package is now implemented in the Arena and AutoMod simulation tools. We also test some random number generators available in popular software environments such as Microsoft's Excel and Visual Basic, SUN's Java, etc., by using them on two very simple simulation problems. They fail the tests by a wide margin.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
 
2
Dieter, U. 1975. How to calculate shortest vectors in a lattice. Mathematics of Computation 29 (131): 827-833.
 
3
Eichenauer-Herrmann, J. 1995. Pseudorandom number generation by nonlinear methods. International Statistical Reviews 63:247-255.
 
4
Eichenauer-Herrmann, J., E. Herrmann, and S. Wegenkittl. 1997. A survey of quadratic and inversive congruential pseudorandom numbers. In Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing, ed. P. Hellekalek, G. Larcher, H. Niederreiter, and P. Zinterhof, Volume 127 of Lecture Notes in Statistics, 66-97. New York: Springer.
5
 
6
Fishman, G. S. 1996. Monte Carlo: Concepts, algorithms, and applications. Springer Series in Operations Research. New York: Springer-Verlag.
7
 
8
 
9
Hellekalek, P., and G. Larcher. (Eds.) 1998. Random and quasi-random point sets, Volume 138 of Lecture Notes in Statistics. New York: Springer.
 
10
 
11
Lagarias, J. C. 1993. Pseudorandom numbers. Statistical Science 8 (1): 31-39.
 
12
Law, A. M., and W. D. Kelton. 1982. Confidence intervals for steady-state simulation, ii: A survey of sequential procedures. Management Science 28:550-562.
 
13
14
 
15
L'Ecuyer, P. 1994. Uniform random number generation. Annals of Operations Research 53:77-120.
 
16
L'Ecuyer, P. 1996a. Combined multiple recursive random number generators. Operations Research 44 (5): 816-822.
 
17
 
18
 
19
 
20
 
21
 
22
 
23
24
 
25
L'Ecuyer, P., and R. Couture. 1997. An implementation of the lattice and spectral tests for multiple recursive linear random number generators. INFORMS Journal on Computing 9 (2): 206-217.
 
26
L'Ecuyer, P., and P. Hellekalek. 1998. Random number generators: Selection criteria and testing. In Random and Quasi-Random Point Sets, ed. P. Hellekalek and G. Larcher, Volume 138 of Lecture Notes in Statistics, 223-265. New York: Springer.
 
27
 
28
29
 
30
 
31
L'Ecuyer, P., R. Simard, E. J. Chen, and W. D. Kelton. 2001. An object-oriented random-number package with many long streams and substreams. Submitted.
 
32
 
33
 
34
Lewis, P. A. W., A. S. Goodman, and J. M. Miller. 1969. A pseudo-random number generator for the system/360. IBM System' s Journal 8:136-143.
 
35
Marsaglia, G. 1985. A current view of random number generators. In Computer Science and Statistics, Sixteenth Symposium on the Interface, 3-10. North-Holland, Amsterdam: Elsevier Science Publishers.
36
37
38
 
39
40
41
 
42
Soto, J. 1999. Statistical testing of random number generators. Available at http://csrc.nist.gov/rng/rng5.html.
 
43
Tausworthe, R. C. 1965. Random numbers generated by linear recurrence modulo two. Mathematics of Computation 19:201-209.
 
44
Tezuka, S. 1995. Uniform random numbers: Theory and practice. Norwell, Mass.: Kluwer Academic Publishers.
45

CITED BY  8
 
 
 
 
 
 


Peer to Peer - Readers of this Article have also read: