Advanced Search

Journal Navigation

Journal Home

Subscriptions

Archive

Contact Us

Table of Contents

CiteULike is a free service for managing and discovering scholarly references - click here to get started.

Sign In to gain access to subscriptions and/or personal tools.
SIMULATION
This Article
Right arrow Full Text (PDF)
Right arrow References
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Alert me to new issues of the journal
Right arrow Add to Saved Citations
Right arrow Download to citation manager
Right arrowRequest Permissions
Right arrow Request Reprints
Right arrow Add to My Marked Citations
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Right arrow Citing Articles via Scopus
Google Scholar
Right arrow Articles by Heikes, R. G.
Right arrow Articles by Rardin, R. L.
Right arrow Search for Related Content
Social Bookmarking
Add to CiteULike   Add to Complore   Add to Connotea   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati   Add to Twitter  
What's this?

Using common random numbers in simulation experiments — an approach to statistical analysis

Russell G. Heikes

School of Industrial and Systems Engineering Georgia Institute of Technology Atlanta, Georgia 30332

Douglas C. Montgomery

School of Industrial and Systems Engineering Georgia Institute of Technology Atlanta, Georgia 30332

Ronald L. Rardin

School of Industrial and Systems Engineering Georgia Institute of Technology Atlanta, Georgia 30332

A widely applied method of experimental design in stochastic simulation is to use the same pseudo random-number stream for each of the systems or alternatives to be compared. If there are only two alternatives, there is a well-known simple method of statistical analysis. This paper presents Graybill's3 extension of that analysis technique to the case of several systems or alternatives and points out its applicability in the simulation environment. The technique is illustrated using a stochastic simula tion model of a small inventory system. An empirical comparison with other methods of design and analysis is included.

SIMULATION, Vol. 27, No. 3, 81-85 (1976)
DOI: 10.1177/003754977602700301
Add to CiteULike CiteULike   Add to Complore Complore   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us   Add to Digg Digg   Add to Reddit Reddit   Add to Technorati Technorati   Add to Twitter Twitter    What's this?


This article has been cited by other articles:


Home page
 SIMULATIONHome page
L. W. Friedman and H. H. Friedman
Comparing simulated alternatives using a distribution-free statistic with blocking by random number stream
SIMULATION, August 1, 1986; 47(2): 68 - 70.
[Abstract] [PDF]

Home page
 Simulation GamingHome page
H. Stanislaw
Tests of Computer Simulation Validity: What do they Measure?
Simulation Gaming, June 1, 1986; 17(2): 173 - 191.
[PDF]