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WSC'00 |
Introduction to Simulation
Jerry Banks
(Brooks Automation, AutoSimulations Division)
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.
Input Modeling
Lawrence M. Leemis (The
College of William and Mary)
Abstract:
Discrete-event simulation models typically have
stochastic elements 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 2000) have
a broader treatment of input modeling than presented here. Nelson et al.
(1995) and Nelson and Yamnitsky (1998) survey advanced techniques.
Tips for Successful Practice of
Simulation
Deborah A. Sadowski (Rockwell Software) and Mark R.
Grabau (Protean Consulting, Inc.)
Abstract:
Succeeding with a technology as powerful as simulation
involves much more than the technical aspects in which you've probably been
trained. The parts of a simulation study that are outside the realm of
modeling and analysis can make or break the project. We explore the most
common pitfalls in performing simulation studies and identify approaches for
avoiding these problems.
Experimental Design for Simulation
W.
David Kelton (University of Cincinnati)
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.
Output Analysis Procedures for Computer
Simulations
David Goldsman (Georgia Institute of Technology) and
Gamze Tokol (Earley Corporation)
Abstract:
This paper concerns the statistical analysis of output
from discrete-event computer simulations. In particular, we discuss problems
involving terminating simulations, the initialization of simulations,
steady-state point and confidence interval estimation for various system
parameters, and comparison among competing system designs.
Simulation-based Optimization
Averill M. Law
and Michael G. McComas (Averill M. Law & Associates, Inc.)
Abstract:
In this tutorial we present an introduction to
simulation-based optimization, which is, perhaps, the “hottest” topic in
discrete-event simulation today. We give a precise statement of the problem
being addressed and also experimental results for two commercial optimization
packages applied to a manufacturing example with seven decision variables.
Verification, Validation, and Accreditation of
Simulation Models
Robert G. Sargent (Syracuse University)
Abstract:
This paper discusses verification, validation, and
accreditation of simulation models. The different approaches to deciding model
validity are presented; how model verification and validation 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; a
recommended procedure is presented; and accreditation is briefly discussed.
Web-Based Modeling and Simulation
S.
Narayanan (Wright State University)
Abstract:
This paper introduces the emerging area of web-based
simulations and presents an overview of the opportunities and challenges in
this field. This introduction begins with an outline of the World Wide Web and
aspects of simulation impacted by advances on the Internet. Next, various
types of applications of web-based simulations are illustrated. This article
concludes with an synopsis of research and development efforts on web-based
simulations, including online simulation documentation, client-side simulation
applets, server-side simulations, and distributed, interactive, web-based
simulators.
Introduction to Manufacturing
Simulation
Scott Miller and Dennis Pegden (Rockwell Software Inc.)
Abstract:
This introductory tutorial presents an overview of
simulation to manufacturing design and scheduling. A review of the modeling
considerations in both application areas is provided. Finally, a number of
example applications will be presented to illustrate the concepts.