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Smart Modeling - Basic Methodology and Advanced
Tools
Arvind Mehta (Lanner Group, Inc.)
Abstract:
The paper discusses how a complex simulation project
can be executed efficiently and effectively following simple basic
methodology, and using advanced modeling features provided by the simulation
tool. The paper explains the methodology that should be followed for the
successful outcome of a simulation project. The paper also discusses and
illustrates some of the advanced modeling capabilities provided by a
simulation tool “Witness”, that enable the user to build complex models very
quickly and at the same time, incorporate desirable characteristics like high
flexibility, sharability and re-usability.
Silk, Java and Object-Oriented
Simulation
Richard A. Kilgore (ThreadTec, Inc.)
Abstract:
Silk® is a set of Java classes that support
object-oriented, general-purpose simulation and animation using the Java
programming language. Silk enables the development of complex, yet manageable
simulations through the construction of usable and reusable simulation
objects. Silk objects are usable because they express the precise behavior of
individual entity-threads from the object perspective using familiar
process-oriented modeling constructs and the object-oriented features of a
general purpose programming language. Silk objects are reusable because they
can be easily archived, edited and assembled using professional Java visual
development environments that support the JavaBeans component architecture.
This introduction describes the fundamentals of designing and creating a Silk
model.
How the ExpertFit Distribution-Fitting Package can make
your Simulation Models more Valid
Averill M. Law and Michael G.
McComas (Averill M. Law and Associates, Inc.)
Abstract:
In this paper, we discuss the critical role of
simulation input modeling in a successful simulation study. Two pitfalls in
simulation input modeling are then presented and we explain how any analyst,
regardless of their knowledge of statistics, can easily avoid these pitfalls
through the use of the ExpertFit distribution-fitting software. We use a set
of real-world data to demonstrate how the software automatically specifies and
ranks probability distributions, and then tells the analyst whether the "best"
candidate distribution is actually a good representation of the data. If no
distribution provides a good fit, then ExpertFit can define an empirical
distribution. In either case, the selected distribution is put into the proper
format for direct input to the analyst's simulation software.
ALPHA/Sim Simulation Software
Tutorial
Kendra E. Moore and Jack C. Chiang (ALPHATECH, Inc.)
Abstract:
ALPHA/Sim is a general-purpose, discrete-event
simulation tool. ALPHA/Sim allows a user to graphically build a simulation
model, enter input data via integrated forms, execute the simulation model,
and view the simulation results, within a single graphical environment. In
this paper, we introduce ALPHA/Sim and describe how to use ALPHA/Sim to build,
simulate, and analyze a simple manufacturing system. In addition, we briefly
describe some advanced features and list some sample applications.
Optimizing Simulations with CSIM18/OptQuest: Finding
the Best Configuration
Herb Schwetman (Mesquite Software, Inc.)
Abstract:
In many cases, a simulation model of a system is used
to evaluate alternative configurations of that system, with the goal of
finding the configuration which maximizes (or minimizes) the value of an
objective while meeting all of the stated requirements. The CSIM18/OptQuest
package automates this kind of search for the best configuration by combining
a powerful simulation engine, CSIM18, and a state-of-the-art optimization
package, OptQuest. This paper describes this integrated package for doing
optimization and simulation. The paper concludes with two examples: finding
the best configuration for a job-shop, and finding the best configuration for
a web server.
Modeling with the Micro Saint Simulation
Package
Daniel Schunk (Micro Analysis and Design, Inc.)
Abstract:
Micro Saint is a discrete-event simulation software
package for building models that simulate real-life processes. With Micro
Saint models, users can gain useful information about processes that might be
too expensive or time-consuming to test in the real world. Some common
application areas for simulation modeling include the following: Modeling
manufacturing processes, such as production lines, to examine resource
utilization, efficiency, and cost; Modeling transportation systems to examine
issues such as scheduling and resource requirements; Modeling service systems
to optimize procedures, staffing and other logistical considerations; Modeling
training systems and their effectiveness over time; Modeling human operator
performance and interaction under changing conditions. Simulation is a
cost-effective way to help show decision-makers the most cost-efficient
alternatives to any problem.
The Extend Simulation Environment
David
Krahl (Imagine That, Inc.)
Abstract:
The Extend modeling environment provides an integrated
structure for building simulation models and developing new simulation tools.
This environment supports simulation modelers on a wide range of levels. Model
builders can use Extend's pre-built modeling components to quickly build and
analyze systems without programming. Simulation tool developers can use
Extend's built-in, compiled language, ModL to develop new modeling components.
All of this is done within a single, self-contained software program that does
not require external interfaces, compilers, or code generators