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Simulation 101 software: workshop and beyond
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Source Winter Simulation Conference archive
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come table of contents
Washington D.C.
SESSION: Simulation 101: simulation 101 table of contents
Pages 233-236  
Year of Publication: 2007
ISBN:1-4244-1306-0
Authors
Barry Lawson  University of Richmond, Richmond, VA
Lawrence Leemis  College of William & Mary, Williamsburg, VA
Sponsors
INFORMS-SIM : Institute for Operations Research and the Management Sciences: Simulation Society
NIST : National Institute of Standards and Technology
(SCS) : The Society for Modeling and Simulation International
ACM/SIGSIM : Association for Computing Machinery: Special Interest Group on Simulation
IIE : Institute of Industrial Engineers
ASA : American Statistical Association
IEEE/SMC : Institute of Electrical and Electronics Engineers: Systems, Man, and Cybernetics Society
Publisher
IEEE Press  Piscataway, NJ, USA
Bibliometrics
Downloads (6 Weeks): 1,   Downloads (12 Months): 29,   Citation Count: 0
Additional Information:

abstract   references   collaborative colleagues  

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ABSTRACT

The C source code associated with the Simulation 101 pre-conference workshop (offered at the 2006 and 2007 Winter Simulation Conferences) is presented here. This paper begins with general instructions for downloading, compiling, and executing the software. This is followed by sections on four groups of the software, categorized by functionality: libraries, Monte Carlo simulations, discrete-event simulations, and utilities. The libraries contain code to generate random numbers, code to generate random variates, and code to evaluate probability density functions, cumulative distribution functions, and inverse distribution functions. The Monte Carlo simulations consist of six programs that estimate various probabilities associated with simple probability problems, some with known analytic solutions and others without analytic solutions. The discrete-event simulations consist of various applications from queueing and inventory systems. Finally, the utilities are used to calculate various point and interval estimators from data sets.


Collaborative Colleagues:
Barry Lawson: colleagues
Lawrence Leemis: colleagues