Smart Modeling - Basic Methodology and Advanced
Arvind Mehta (Lanner Group, Inc.)
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
Richard A. Kilgore (ThreadTec, Inc.)
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.)
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
Kendra E. Moore and Jack C. Chiang (ALPHATECH, Inc.)
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.)
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
Daniel Schunk (Micro Analysis and Design, Inc.)
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.)
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