Law Averill M., McComas Michael G. How the expertfit distribution-fitting package can make your simulation models more valid // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.253-258.
This paper discuss the critical role of simulation input modeling in a successful simulation study.

Law, A.M., McComas, M.G. (2000). Simulation-based optimization // In Proceedings of the 2000 Winter Simulation Conference, pp. 46-49.

Law Averill M., McComas Michael G. Simulation-based optimization // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.46-49.
In this article authors represent 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.

Leemis Lawrence.. Input modeling // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.17-25.
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 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.

Legrand Iosif C., Newman Harvey B. The monarc toolset for simulating large network-distributed processing systems // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.1794-1801.

Lemieux Christiane, L’Ecuyer Pierre. Using lattice rules for variance reduction in simulation // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.509-516.
Quasi-Monte Carlo methods are designed to improve upon the Monte Carlo method for multidimensional numerical integration by using a more regularly distributed point set than the i.i.d. sample associated with Monte Carlo. Lattice rules are one family of quasi-Monte Carlo methods, originally proposed by Korobov in 1959. In this paper, we explain how randomized lattice rules can be used to construct efficient estimators for typical simulation problems, and we give several numerical examples. We are interested in two main aspects: Studying the variance of these estimators and finding which properties of the lattice rules should be considered when defining a selection criterion to rate and choose them. Numerical results for three different problems illustrate how this methodology typically improves upon the usual Monte Carlo simulation method.

Li Janice P. Train station passenger flow study // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.1173-1176.
With the increasing demand for public transportation due to congested highways, trains have become one of the most viable alternatives, especially for daily commuting. While transit agencies are excited with the increasing ridership, they are also challenged with a higher volume of passenger flow and longer queuing lines at the existing stations. To improve the current situation and plan for the future, transit agencies are using simulation tools to help evaluate station design, queue management, fare equipment design and fare policy impacts.

Peter Lorenz. Web-basierte Simulation und HLA in H.Szczerbicka und Th.Uthmann (Hrsg.): Modellierung- Simulation und Künstliche Intelligenz. SCS Europe BVBA Ghent 2000, p.417-436.

P. Lorenz, B.B. Müller, R. Freudenberg, H. Gebhardt, H. Herper, H. Peters, A. Saßmannshausen. Methodenentwicklung zur präventiven Abschätzung der Belastungsituation und des Gefahrenpotentials bei geänderten Arbeitsstrukturen unter Zuhilfenahme der Simulationstechnik. ISBN 3-9804874-0-7. Magdeburg 2000.

Lu T., Chungnan L., and Hsia W. 2000. Supporting large-scale distributed simulation using HLA // ACM Trans. Model. Comput. Simul. 10, 3, P.268–294.

Marr Charles, Storey Christopher, Biles William E., KleijnenA Jack P.C. Java-based simulation manager for web-based simulation // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.1815-1822.
This paper discusses a Web-based simulation manager program that executes an Application Service Provider event for a customer who does not possess the in house capability to program complex simulations.

Marzouk Mohamed, Moselhi Osama. Optimizing earthmoving operations using object-oriented simulation // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.1926-1930.
This paper presents an automated system for optimizing earthmoving operations. The proposed system can assist earthmoving contractors, during bid preparation stage, in estimating the time and cost required in order to accomplish the task at hand. It also provides a methodology for recommending the most suitable equipment fleet that satisfies the job requirements and the stated objectives of contractors.

Mason Colin R., Moffat James. Representing the C2 process in simulations: modelling the human decision-maker // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.940-949.

McGraw Robert M., MacDonald Richard A. Abstract modeling for engineering and engagement level simulations // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.326-334.

Medeiros D.J., Traband Mark, Tribble April, Lepro Rebekah, Fast Kenneth, Williams Daniel. Simulation based design for a shipyard manufacturing process // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.1411-1414.
Discrete event simulation can be used for virtual prototyping of new manufacturing facilities. Models built for this purpose must be easy to use, flexible, and provide a realistic graphical view of the proposed system. The DESTINY project has developed models of plate processing operations to assist shipyards in modernizing their plate fabrication lines. Configuration information for a proposed line is collected via a Web interface, which then launches a program to build and execute a simulation of the system. Graphics images and statistical reports are then returned to the user via the Web interface. The approach allows rapid analysis of technology improvements and a visualization of proposed system operation.

Mehta Arvind. Smart modeling – basic methodology and advanced tools // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.241-245.
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.

Merkuryeva G., Tolujev J. Computer Simulation and Metamodelling of Logistics Processes at a Container Terminal // Studies in Informatics and Control. 2000. Vol. 9, No. 1. P. 53-60.

Metz Michael L. Joint warfare system (JWARS) verification and validation lessons learned // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.855-858.
JWARS V&V (a joint venture of Innovative Management Concepts in Sterling VA and BMH Associates in Norfolk VA) has been responsible for conducting the verification and validation (V&V) of the JWARS simulation since September of 1997. This paper describes the lessons learned during the conduct of the effort including: the JWARS V&V process, the JWARS V&V Plan, reports delivered, and results to date. Special emphasis is on the use of the DoD VV&A Recommended Practices Guide as a basis of JWARS V&V planning and procedures and the evolution of the JWARS V&V Integrated Product Team.

Miller Scott, Pegden Dennis. Introduction to manufacturing simulation // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.63-66.
This article represents 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.

Mizuta Hideyuki, Steiglitz Ken. Agent-based simulation of dynamic online auctions // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.1772-1777.
The need to understand dynamic behavior in auctions is increasing with the popularization of online auctions. Applications include designing auction mechanisms, bidding strategies, and server systems. We describe simulations of a typical online auction, where the duration is fixed, and the second-highest price is continuously posted and determines the winner’s payment. We modeled agents of exactly two types, idealizations and simplifications of those observed in practice: early bidders, who can bid any time during the auction period, and snipers, who wait till the last moments to bid.

Moore Kendra E., Chiang Jack C. ALPHA/Sim simulation software tutorial // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.259-267.
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.

Mota Edjair, Wolisz Adam, Pawlikowski Krzysztof. A perspective of batching methods in a simulation environment of multiple replications in parallel // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.761-766.
Discrete event simulation is frequently time-consuming either because modern dynamic systems, such as telecommunication networks, are becoming increasingly complex and/or a great number of observations is required to yield reasonably accurate results. An interesting approach to reduce the time duration of simulation is that of concurrently running multiple replications in parallel on a number of processors connected via networking and averaging the results adequately. We present the results of our research on the suitability of batch-means-based procedures in such distributed stochastic simulation.

Mullarkey Peter, Gavirneni Srinagesh, Morrice Douglas J. Dynamic output analysis for simulations of manufacturing environments // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.1290-1296.
We describe the design and implementation of a generic, real-time, in-line output analysis procedure for controlling simulations of discrete manufacturing environments. We implemented this capability in the commercial simulation software Extend. The main issues we faced were (1) Specifying the products to evaluate, (2) Determining the batch sizes for output analysis, and (3) Defining the stopping conditions based on the confidence intervals.

Nam Kyoo Boots, Shahabuddin Perwez. Simulating GI/GI/1 queues and insurance risk processes With subexponential distributions // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.656-665.
This paper deals with estimating small tail probabilities of the steady-state waiting time in a GI/GI/1 queue with heavy-tailed (subexponential) service times.

Nance Richard E. Simulation education: past reflections and future directions // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.1595-1601.
The results of two surveys of persons concerned with simulation education in the 1974-76 timeframe are compared with the results of a 1997 workshop entitled, .What Makes a Modeling and Simulation Professional? Analysis of these two samplings, separated in time by over 20 years and admittedly with differing objectives and under dissimilar conditions, is used to identify persistent issues, beliefs or convictions regarding the needs for professionals. The intent is to establish a departure point for further discussion of simulation education.

Narayanan S. Web-based modeling and simulation // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.60-62.
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 WWW and aspects of simulation impacted by advances on the Internet. Next, various types of applications of web-based simulations are illustrated. 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.

Oren Tuncer I., Numrich S. K., Uhrmacher Adelinde M., Wilson Linda F., Gelenbe Erol. Agent-directed simulation – challenges to meet defense and civilian requirements // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.1757-1762.

Owen Larry E., Zhang Yunlong, Rao Lei, McHale Gene. Traffic flow simulation using CORSIM // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.1143-1147.
This paper presents an overview of the concept and features of the CORSIM traffic simulation program and the TSIS package that provides an integrated, user-friendly interface and environment for executing CORSIM. The new functions and feature of CORSIM and TSIS in the most recent release are highlighted. Several successful TSIS/CORSIM applications are used to demonstrate that CORSIM is a very effective tool to perform traffic operations analysis and to evaluate new ITS technologies.

Panayiotou Christos G., Cassandras Christos G., Wei-Bo Gong. Model abstraction for discrete event systems using neural networks and sensitivity information // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.335-341.
In this paper, we investigate the use of sensitivity information to reduce the simulation effort required for training a Neural networks metamodel.

Paprotny Igor, Shiau Juin-Yan, Huh Yo, Mackulak Gerald T. Simulation based comparison of semiconductor AMHS alternatives: continuous flow vs. overhead monorail // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.1333-1338.

Pawlikowski Krysztof, Kreutzer Wolfgang. Integrating modelling and data analysis in teaching discrete event simulation // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.1645-1650.
This paper argues for the importance of teaching those issues that critically affect the analysis and credibility of a simulation results alongside those methods and tools targeted at the needs of model design and construction.

Phelps Richard A., Parsons David J., Siprelle Andrew J. The SDI industry product suite: simulation from the production line to the supply chain // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.280-214.
The SDI Industry®Product Suite is a versatile, high-level simulation toolset for solving problems of whole enterprises. It adds important capabilities to an existing simulation package, Extend, which provides a robust simulation architecture and a wealth of existing building blocks. The SDI Industry Product Suite contains 5 specific elements for modeling the enterprise: SDI Database for high-speed data import/export; SDI Industry for highspeed, high-volume production line modeling; SDI Plant Builder for multi-stage plants driven by schedules; and Supply Chain Builder for supply/distribution chains.

Pidd M., Cassel R. A., Using Java to Develop Discrete Event Simulations, The Journal of the Operational Research Society, Vol. 51, No. 4, 2000, P.405-412.

Pritchett Amy R., Lee Seungman, Huang David, Goldsman David. Hybrid-system simulation for national airspace system safety analysis // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.1132-1142.
This paper describes the development of a simulation architecture meeting these criteria. The issues with its development are described conceptually, and its application to the task of safety analysis of the national airspace system is discussed. In particular, an object-oriented approach to hybrid-system simulation is detailed, and computationally efficient methods of updating the simulation are described and compared.

Rabbath C.A., Abdoune M., Belanger J. Effective real-time simulations of event-based systems // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.232-238.
This paper presents a set of novel tools that allow the efficient simulation, at fixed time steps, of event-based dynamic systems.

Rehn Gordon D. Simulation in daily factory operation: “setting the line bogey in Augusta” // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.1380-1384.
This paper describes the simulation tool structure designed for John Deere Augusta Works, and discusses the circumstances surrounding this unique simulation application. Included in the discussion are the benefits derived from the application; the critical success factors enabling its use; lessons learned in converting a simulation analysis into an operating tool; and future improvements envisioned.

Richter H. and März L. (2000). Toward a standard process: the use of UML for designing simulation models // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). Piscataway, NJ: IEEE, pp. 394-398.

Rodionov A.S. Ways of evolution of discrete event simulation systems // The 2nd International Workshop on Computer Science and Information Technologies (CSIT-2000), USATU Scientific Session. Ufa, 2000. P. 218-220.

Rodrigues Marcelo B., Karpowicz Mario, Kang Keebom. A readiness analysis for the Argentine air force and the Brazilian NAVY A-4 fleet via consolidated logistics support // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.1068-1074.
The Argentine Air Force and the Brazilian Navy recently added the Douglas A-4 Skyhawk aircraft to their military services. Each country maintains its own limited repair facility and spare parts inventory. Major repair work must be sent to the manufacturers in the United States, and the long repair cycle times adversely affect military readiness. It is critical to implement an effective spare parts management system to compensate for such long repair cycle times. We developed a simulation model to study the impact of consolidating aviation component spare parts inventory management and reducing transportation cycle times.

Rohrer Matthew W.. Automod tutorial // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.170-176.

Rosenberger Jay M., Schaefer Andrew J., Goldsman David, Johnson Ellis L., Kleywegt Anton J., Nemhauser George L. Simair: a stochastic model of airline operations // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.1118-1122.
Airline transportation systems are inherently random. However, airline planning models do not explicitly consider stochasticity in operations. Because of this, there is often a notable discrepancy between a schedule’s planned and actual performance. SimAir is a modular airline simulation that simulates the daily operations of a domestic airline. Its primary purpose is to evaluate plans, such as crew schedules, as well as recovery policies in a random environment. We describe the structure of SimAir, and we give future directions for the study of airline planning under uncertainty.

Rossetti Manuel D., Aylor Ben, Jacoby Ryan, Prorock Alyson. Simfone: an object-oriented simulation framework // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.1855-1864.
This paper presents an overview of a software design framework for the development of object-oriented simulations. The framework is documented using the Unified Modeling Language and is divided into packages to organize the collection of classes into important functional areas. The purpose of the framework is two-fold. First, the framework is useful in understanding the concepts and abstractions within simulation modeling and languages. Secondly, the framework can serve as the basis for the development of object-oriented simulation libraries. We illustrate the latter through a Java implementation.

Ruiz-Torres Alex J., Zapata Edgar. Simulation based operational analysis of future space transportation systems // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.1123-1131.
This paper presents an approach to the operational analysis of future space transportation systems. The model proposed under this approach utilizes expert knowledge to predict the operational requirements of a vehicle concept, including the ground activities, flows, resources, and costs; all the components of the spaceport. The model incorporates simulation in order to include spaceport characteristics as alternative flows, processing variability, and other random events. This model will provide vehicle designers with useful understanding of the spaceport operations related to the investigated vehicle design.

Rybin Erwin, Breitenecker Felix. Simulation of a production plant in the brick industry // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.1915-1918.
The paper deals with a simulation study on a planned production plant in the brick industry. We implemented this plant in TAYLOR II. Although the boundary conditions seemed relatively simple, we had to manage a complex, non-linear system. For this reason we implemented .dynamic priority. to the main part of the system, the travelling crane. Still this sophisticated logic was not enough to guarantee good operation, because insome situations the system runs out of capacity. We then gave recommendations how to improve the situation for a perfect operation of the production system. For this purpose we finally made an analysis of the necessary investment costs against the running costs caused by system breakdown.

Sadowski Deborah A., Grabau Mark R. Tips for successful practice of simulation // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.26-31.
Succeeding with a technology as powerful as simulation 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 We explore the most common pitfalls in performing simulation studies and identify approaches for avoiding these problems.

Sanchez Susan M., Ferrin David M., Ogazon Tom, Sepúlveda José A., Ward Timothy J. Emerging issues in healthcare simulation // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.1999-2003.
Despite the size and importance of the health care industry, simulation is less prevalent in health care than in other fields such as manufacturing, logistics, and military applications. Yet simulation clearly has the potential to play a role in health care decision-making at many levels. The purpose of this panel is to discuss some of the issues that practioners must be aware of in order to tap the potential of simulation in the health care arena. The panelists have extensive experience in health care and the use of simulation in that environment. They have provided statements outlining several key issues for achieving success in current and future health care simulation projects.

Sargent Robert G. Verification, validation, and accreditation of simulation models // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.50-59.
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.

Sargent Robert G., Glasow Priscilla A., Kleijnen Jack P.C., Law Averill M., McGregor Ian, Youngblood Simone. Strategic directions in verification, validation, and accreditation research // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.909-916.
Six simulation professionals present their views on the directions that they believe that verification, validation, and accreditation research should take. Two of the six are active verification, validation, and accreditation researchers from academia, two develop industry simulation models, and two work in verification, validation, and accreditation of military simulation models. A number of areas and topics for research in verification, validation, and accreditation are identified. It appears that application domains of simulation models affect what topics need verification, validation, and accreditation research.

Sawhney Anil, Deshpande Hemant, Mund André. Javabeans-based framework for construction simulation // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.1919-1925.
This paper describes a prototype component-based architecture for construction simulation. It highlights the work performed by the authors in using JavaBeans for the simulation of construction processes.

Schriber Thomas J., Brunner Daniel T. Inside discrete-event simulation software: how it works and why it matters // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.90-100.
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 management. The implementation of these generic ideas in AutoMod, SLX, and Extend 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 (Arena), ProModel, and GPSS/H as well as the other three tools.

a href="http://simulation.su/uploads/files/default/2000-schruben-1.pdf" target="_blank">Schruben Lee W. Mathematical programming models of discrete event system dynamics // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.381-385.
Analytical models for the dynamics of some discrete event systems are introduced where the system trajectories are solutions to linear and mixed-integer programs.

Schulze Thomas, Schumann Marco, Gordon D. Rehn. Language based simulation models as management tools for assembly lines // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.1393-1401.
This paper demonstrates that despite the trend to Point & Click environments, the traditional approach of using general-purpose simulation languages is still eligible. The authors share their experiences gained from building a complex simulation using the language SLX. On the basis of examples from the projects, the efficient modeling features of the SLX languages are highlighted.

Schunk Daniel. Modeling with the micro saint simulation package // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.274-279.
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. Simulation is a cost-effective way to help show decision makers the most cost-efficient alternatives to any problem.

Schunk Daniel, Plott Beth. Using simulation to analyze supply chains // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.1095-1100.
This paper will demonstrate what some of the considerations are in using Supply Solver to help solve supply chain design problems.

Schwetman Herb. Optimizing simulations with CSIM18/OptQuest: finding the best configuration // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.268-273.
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 jobshop, and finding the best configuration for a web server.

Seila Andrew F. Medical education as a model for simulation education // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.1624-1629.
Simulation professionals need to see themselves first as systems analysts, i.e., problem solvers, rather than just simulation users. As the networked digital economy develops, systems will become more complex, creating a robust market for experienced systems analysts who use simulation to solve operational problems and manage these complex systems. Physicians solve problems involving a complex biological system, i.e., the human body. The medical education system in the United States is examined and proposed as a model for an education structure for professional systems analysts. The objectives and requirements of simulation education are examined and a curriculum structure is proposed. It is also argued that certifying exams would do much to promote the profession and improve the educational environment.

Smith III Raymond L., Roberts Stephen D. A voice assisted simulation-animation architecture // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.1201-1210.
This paper introduces a software architecture that has been used to enable voice assistance for a simulation-animation environment by integrating technologies that recognize spoken language input and generate spoken language output.

Stahl Ingolf. How should we teach simulation? // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.1602-1612.
This paper deals with the issue of how one can teach simulation in the most time-efficient way. We first distinguish between different types of student as regards their background and future needs. We next look at reasons for studying simulation at a business school. Next we compare animation oriented simulators with simulation languages. We then study a list of desirable criteria for simulation software, in particular simulation languages, that should be used in education. We finally answer the question if there is any system that fulfills all of these criteria.

Standridge Charles R., Heltne David R. An MSE-based simulation capability for strategic and tactical logistics // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.1107-1113.

Steiger Natalie M., Wilson James R. Experimental performance evaluation of batch means procedures for simulation output analysis // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.627-636.

Sudra Rajeev, Taylor Simon J.E., Janahan Tharumasegaram. Distributed supply chain simulation in GRIDS // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.356-361.

Surdu John R., Hill John M.D., Pooch Udo W. Anticipatory planning support system // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.950-957.
This paper presents a methodology for building an automated system to support Anticipatory Planning.

Takakuwa Soemon, Takizawa Hiroki, Ito Kumiko, Hiraoka Shinichiro. Simulation and analysis of non-automated distribution warehouses // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.1177-1184.
The distribution warehouse is located between manufacturers and customers. Storage facilities are designed around four primary functions: holding, consolidation, break-bulk, and mixing. In addition, materials handling within a storage-handling system reduces to three primary activities: loading and unloading, movement to and from storage, and order filling. Generally, it is more difficult to build a simulation model for a non-automated warehouse than for AS/RS, because materials handling is much more complicated. In this study, a procedure to build simulation models for move store activities of complicated and non-automated distribution warehouses is proposed. The simulation model here is designed to execute together with the program for generating parameters of materials handling.

Taranto Sarah E., Harper Ann M., Edwards Erick B., Rosendale John D., McBride Maureen A., Daily O. Patrick, Murphy Dan, Poos Bill, Reust Janet, Schmeiser Bruce. Developing a national allocation model for cadaveric kidneys // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.1971-1977.
The UNOS Kidney Allocation Model (UKAM) is a software tool for the simulation and analysis of national cadaveric kidney and kidney-pancreas allocation policies for transplantation. UKAM is modular and is designed to enable easy updating of the various components as new data become available. UKAM.s flexibility gives the user the ability to create and evaluate an almost infinite number of detailed allocation policies. This will enable the United Network for Organ Sharing (UNOS) to make decisions based on quantitative data when considering changes in organ allocation policies.

Taylor James G., Yildirim Ugur Ziya, Murphy William S. Hierarchy-of-models approach for aggregated-force attrition // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.925-932.
This paper presents some innovations for overcoming shortcomings in the current state-of-the-art for the hierarchy-of-models approach to modeling aggregated force attrition in ground-combat models. The basic concept of such an approach for modeling large-scale system behavior is presented, together with the theoretical underpinnings for modeling attrition in large-scale ground combat.

van Burgsteden Marco C., Joustra Paul E., Bouwman Michiel R., Hullegie Mark. Modeling road traffic on airport premises // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.1154-1163.
This paper describes the development of a traffic-modeling tool as an Arena template and two applications of it: one to evaluate alternative designs for the road network on the premises of Amsterdam Airport Schiphol and one to assess the effects of traffic signaling on a junction. The tool uses discrete event simulation, very suited for modeling traffic in areas where there are a lot of interactions other than car following. Generation of the O/D matrix was done automatically by a custom-made application.

Van Dijk Nico M. On hybrid combination of queueing and simulation // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – pp.147-150.
This paper aims to and illustrate that simulation and queuing theory can and should go hand in hand for a variety of practical problems, both in daily-life and industry, which are still open for fundamental research. To this end, it will highlight real-life cases taken from: Daily-life situations (postal office or bank), administrative logistics (reengineering), transportation (railways), and call center analysis.

White K. Preston, Cobb Michael J., Spratt Stephen C. A comparison of five steady-state truncation heuristics for simulation // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.755-760.

Wiedemann Thomas. A virtual textbook for modeling and simulation // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.1660-1665.
The goal of this paper is to present a real working database system for managing links and generating collections of simulation related material for teaching and learning purposes.

Wiedemann Thomas. VISUALSLX – an open user shell for high-performance modeling and simulation // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.1865-1871.
This paper reveals the architecture and the underlying data structures of the system. Additional requirements and interfaces are caused by the application of VisalSLX as a web-based modeling and simulation system.

Wilensky U., Stroup W. (2000). Networked gridlock: Students enacting complex dynamic phenomena with the HubNet architecture // Proceedings of the Fourth Annual International Conference of the LearningSciences, Ann Arbor, MI, June 14 - 17.

Wilensky U., Centola D. (2007, based on 2000 paper). Simulated Evolution: Facilitating Students' Understanding of the Multiple Levels of Fitness through Multi-Agent Modeling // Paper presented at the Evolution Challenges conference, Phoenix, AZ, November 1-4.

Withers David H. Software engineering best practices applied to the modeling process // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.432-439.
We present a mapping of Best Practices from the field of software engineering to the practice of discrete event simulation model construction. There are obvious parallels between the two activities. We therefore hypothesize there should be opportunities to improve the model construction process by taking advantage of these parallels. This research extends the prior work (Withers 1993) that provided a structured definition of the modeling process.

Wooldridge M., Jennings N. R., David K. The Gaia Methodology for Agent-Oriented Analysis and Design // Journal of Autonomous Agents and Multi-Agent Systems 3, pp. 285-312, 2000.

Workman Russell W. Simulation of the drug development process: a case study from the pharmaceutical industry // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.1995-1998.
This paper uses a case study from the pharmaceutical industry to show how simulation modeling can be applied to understanding large, highly-complex processes such as drug development.

Yeh Yingchieh, Schmeiser Bruce. Simulation output analysis via dynamic batch means // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.637-645.
This paper is focused on estimating the quality of the sample mean from a steady-state simulation experiment with consideration of computational efficiency, memory requirement, and statistical efficiency.

Young Hae Lee, Sook Han Kim. Optimal production-distribution planning in supply chain management using a hybrid simulation-analytic approach // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.1252-1259.
In this paper, we propose a hybrid approach which is a specific problem solving procedure combining analytic and simulation methods to solve production-distribution problems in supply chains. The machine capacity and distribution capacity constraints in the analytic model are considered as stochastic factors and are adjusted by the proposed specific process according to the results from an independently developed simulation model which includes general production-distribution characteristics.

Zayed Tarek M., Halpin Daniel W. Simulation as a tool for resource management // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.1897-1906.
In this paper, simulation is applied to a Concrete Batch Plant to analyze alternative solutions and resource management.

Zeigler Bernard P., Sarjoughian Hessam S. Creating distributed simulation using devs M&S environments // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.158-160.
The modelling and simulation theory is considered and its support for constructing distributed simulations. Formal representation of simulation models can contribute to a number of aspects in the modeling and simulation enterprise. Separation of models from simulation execution engines is a prerequisite transferring model among phases of a project as well as from project to project. The Discrete Event System Specification formalism, drawing on its system theoretic basis, provides a number of important properties such as hierarchical, modular composition, universality and uniqueness that can support development of simulation models and environments their development.

Zülch Gert, Fischer Jörg, Jonsson Uwe. An integrated object model for activity network based simulation // In: Proceedings of the 2000 Winter Simulation Conference (Joines, J.A, Barton, R.R., Kang, K. and Fishwick, P.A., eds). – 2000. – P.371-380.
This paper describes an object-orientated simulation approach towards an integrated planning of production systems.