INTRODUCTION TO SIMULATION  
 
  Jerry Banks
 
AutoSimulations, Inc.
Atlanta, Georgia 30067
 
 
ABSTRACT
 
This introduction begins with an example of simulation done by hand. Modeling concepts in simulation are then introduced based on the example. Next, the advantages and disadvantages of simulation are discussed. The introduction ends with a discussion of the steps in a simulation study.
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SIMULATION INPUT MODELING  
 
  Lawrence Leemis
 
Department of Mathematics
College of William & Mary
Williamsburg, VA 23187--8795, U.S.A.
 
 
ABSTRACT
 
Discrete-event simulation models typically have stochastic components that mimic the probabilistic nature of the system under consideration. Successful input modeling requires a close match between the input model and the true underlying probabilistic mechanism associated with the system. The general question considered here is how to model an element (e.g., arrival process, service times) in a discrete-event simulation given a data set collected on the element of interest. For brevity, it is assumed that data is available on the aspect of the simulation of interest. It is also assumed that raw data is available, as opposed to censored data, grouped data, or summary statistics. Most simulation texts (e.g., Law and Kelton 1991) have a broader treatment of input modeling than presented here.
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ABC'S OF OUTPUT ANALYSIS  
 
  Susan M. Sanchez
 
Management Science & Information Systems
School of Business Administration
University of Missouri -- St. Louis
8001 Natural Bridge Rd.
St. Louis, MO 63121-4499
 
 
ABSTRACT
 
We present a brief overview of several of the basic output analysis techniques for evaluating stochastic dynamic simulations. This tutorial is intended for those with little previous exposure to the topic, for those in need of a refresher course, and especially for those who have never heard of output analysis. We discuss the reasons why simulation output analysis differs from that taught in basic statistics courses, and point out how to avoid common pitfalls that may lead to erroneous results and faulty conclusions.
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DESIGNING SIMULATION EXPERIMENTS  
 
  W. David Kelton
 
Department of Quantitative Analysis and Operations Management
College of Business Administration
University of Cincinnati
Cincinnati, OH 45221-0130, U.S.A.
 
 
ABSTRACT
 
This tutorial introduces some of the ideas, issues, challenges, solutions, and opportunities in deciding how to experiment with a simulation model to learn about its behavior. Careful planning, or designing, of simulation experiments is generally a great help, saving time and effort by providing efficient ways to estimate the effects of changes in the model's inputs on its outputs. Traditional experimental-design methods are discussed in the context of simulation experiments, as are the broader questions pertaining to planning computer-simulation experiments.
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VALIDATION AND VERIFICATION OF SIMULATION MODELS  
 
  Robert G. Sargent
 
Simulation Research Group
Department of Electrical Engineering and Computer Science
College of Engineering and Computer Science
Syracuse University
Syracuse, New York 13244
 
 
ABSTRACT
 
This paper discusses validation and verification of simulation models. The different approaches to deciding model validity are presented; how model validation and verification relate to the model development process are discussed; various validation techniques are defined; conceptual model validity, model verification, operational validity, and data validity are described; ways to document results are given; and a recommended procedure is presented.
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A TUTORIAL ON SIMULATION IN HEALTH CARE: APPLICATIONS AND ISSUES  
 
  Charles R. Standridge
 
Padnos School of Engineering
Grand Valley State University
301 West Fulton
Grand Rapids, MI 49504-6495, U.S.A.
 
 
ABSTRACT
 
Simulation is an ideal tool for addressing wide ranging issues in health care delivery. These issues involve public policy, patient treatment procedures, capital expenditure requirements, and provider operating policies.
 
This tutorial presents example applications in each of these areas. Modeling, experimentation, and other project issues are discussed. A summary of technical issues, as well as issues relating to the acceptance of the use of simulation in health care delivery, is presented.
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SIMULATION OF MANUFACTURING SYSTEMS  
 
  Averill M. Law
Michael G. McComas

 
Averill M. Law & Associates, Inc.
P.O. Box 40996
Tucson, Arizona 85717
 
 
ABSTRACT
 
This paper discusses how simulation is used to design new manufacturing systems and to improve the performance of existing ones. Topics to be discussed include: manufacturing issues addressed by simulation, simulation software for manufacturing applications, techniques for building valid and credible models, and statistical considerations. A comprehensive example will be given in the conference presentation.
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TIPS FOR SUCCESSFUL PRACTICE OF SIMULATION  
 
Deborah A. Sadowski
 
Systems Modeling Corporation
504 Beaver Street
Sewickley, Pennsylvania 15143, U.S.A.
  Mark R. Grabau
 
Andersen Consulting
1666 K Street, N.W.
Washington, DC 20006-2873 U.S.A.
 
ABSTRACT
 
Remember back in school what it was like to learn new concepts? At the time, it probably seemed challenging, even intimidating. Little did you know, though, that it was nothing compared with doing the same in the "real world."
 
Succeeding with a technology as powerful as simu-lation involves much more than the technical aspects you may have been trained in. The parts of a simulation study that are outside the realm of modeling and analysis can make or break the project. And, of course, you need to do a responsible job of those "easy" parts-building the model, verifying and validating it, and analyzing your results-as well!
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APPLYING SIMULATION IN A CONSULTING ENVIRONMENT - TIPS FROM AIRPORT PLANNERS  
 
  Willard C. Hewitt, Jr.
Eric E. Miller

 
TransSolutions
14600 Trinity Blvd., Suite 200
Fort Worth, TX 76120
 
 
ABSTRACT
 
This paper describes the typical steps performed in a simulation consulting project in the aviation industry. While the aviation consulting environment does require some differences in the specific approach, the general framework has been applied successfully in the more traditional areas of logistics and manufacturing.
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INSIDE DISCRETE-EVENT SIMULATION SOFTWARE: HOW IT WORKS AND WHY IT MATTERS  
 
Thomas J. Schriber
 
Computer and Information Systems
The University of Michigan
Ann Arbor, Michigan 48109-1234, U.S.A.
  Daniel T. Brunner
 
Systemflow Simulations, Inc.
6366 Guilford Avenue, Suite 300
Indianapolis, Indiana 46220-1750, U.S.A.
 
ABSTRACT
 
This paper provides simulation practitioners and consumers with a grounding in how discrete-event simulation software works. Topics include discrete-event systems; entities, resources, control elements and operations; simulation runs; entity states; entity lists; and entity-list manage-ment. The implemen-tation of these generic ideas in AutoMod and SLX is described. The paper concludes with several examples of "why it matters" for modelers to know how their simulation software works, including coverage of SIMAN, ProModel and GPSS/H as well as the other two tools.
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