Paul M. Julich, PhD
GE-Harris Railway Electronics
Box 8900
Melbourne,FL 32902-8900, U.S.A.
Stephen L. Brazelton
GE-Harris Railway Electronics
Box 8900
Melbourne,FL 32902-8900 U.S.A.
Charles G. Martin
CSX Transportation
500 Water Street
Jacksonville, FL 32202
Daniel F. Curtiss
GE-Harris Railway Electronics
Box 8900
Melbourne,FL 32902-8900 U.S.A.
Railroads have large investments in capital items such as track, trains, and terminals. Optimizing the use of their resources has the potential of enormous payback. Precision Train Control™ (PTC) is an effort to optimize the flow of trains on the line of road in order to increase the return on capital.
This paper describes a study whose purpose was to quantify the performance improvements that could be anticipated with PTC. A large-scale simulation involving approximately 1000 miles of track and 700 trains was conducted to produce an estimate of potential improvement.
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Jack B. Homer
Homer Consulting
36 Covington Lane
Voorhees, NJ, 08043, U.S.A.
Natasha O. Lukiantseva
David W. Bell
CSX Transportation
Jacksonville, FL, 32202, U.S.A.
Thomas E. Keane
Norbridge, Inc.
30 Monument Square
Concord, MA, 01742, U.S.A
This paper describes the context for and creation of a strategic planning model of a major U.S. railway. The key factors in choosing a system dynamics approach are presented, and the synergy between the new model and the existing suite of planning applications is highlighted. The overall structure of the model is reviewed, including the key reinforcing and balancing loops, and model creation issues such as level of aggregation are discussed. The methodology followed in the data collection and calibration phases is described in detail, and samples of calibration metrics and sensitivity testing parameters are provided, as well as sample model output. Lastly, potential future uses of the model are noted.
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  Harald Krueger
Canadian National Railway
935 de La Gauchetiere Street West
Montreal, Quebec H9H 3P8, CANADA
This paper describes the development and application of a Parametric Model at Canadian National Railway (CN) for use in rail capacity planning. The Parametric Capacity Model is a practical tool used to help improve track asset utilization through the measurement and monitoring of system track capacity.
Understanding capacity is essential for determining the amount of traffic that can be moved over a rail system and degree of service & reliability that can be expected. The Parametric Capacity Model was developed to provide this understanding by measuring Theoretical, Practical, Used & Available track capacity.
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CSCAT: The Compaq Supply Chain Analysis Tool  
Ricki G. Ingalls
Global Integrated Logistics
Compaq Computer Corporation
20555 SH 249
Houston, TX 77070
Cynthia Kasales
Systems Modeling Corporation
The Park Building
504 Beaver Street
Sewickley, PA 15143
In today's business environment, the dynamics of the business drive many decisions in the supply chain. Companies will buffer inventory, carry excess capacity and headcount, and have costly marketing initiatives in order to handle the dynamics of the business. In order to better analyze the business dynamics and define supply chains that are robust to changes in the business environment, Compaq has developed an internal package, called the Compaq Supply Chain Analysis Tool (CSCAT). CSCAT is an ARENA® discrete-event simulation that allows for the easy configuration of a supply chain and the analysis of the dynamics of a supply chain. CSCAT has been used in Compaq to address strategic supply chain issues and certain product-specific supply chain issues. This paper gives an overview of CSCAT.
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Supply Chain vs. Supply Chain:
Using Simulation to Compete Beyond the Four Walls  
  George Archibald
Nejat Karabakal
Paul Karlsson
IBM Corporation
140 East Town Street
Columbus, Ohio 43215 U.S.A.
It has been said in this world of virtual corporations that it is no longer companies that compete, but supply chains. When you look at the model of a corporation today, the traditional vertically integrated business seems to be a thing of the past. A prime example of this is Nike. They own no factories, trucks, or stores, yet are one of the world's most successful retail firm. Today's supply chains reflect this trend in that few firms control the entire supply chain from end to end. Most companies rely on a mix of suppliers, transportation resources, assemblers, warehousing firms, and retail outlets to bring their product to the market. As a result of this mix of outside firms, it is often difficult to know the impact of changes or poor performance on the supply chain. What is needed is a tool that can give visibility of the entire supply chain that allows for the testing of numerous "what if" scenarios such as outsourcing, consolidating vendors, collaborative planning, or implementing e-business. Only with this capability will you and all of your supply chain partners be able to effectively compete against your competitors' supply chains.
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A Four Step Methodology for Using Simulation and Optimization Technologies in Strategic Supply Chain Planning  
  Donald A. Hicks
President and CEO
LLama-Soft, Inc.
Supply chains are real world systems that transform raw materials and resources into end products that are consumed by customers. Supply chains encompass a series of steps that add value through time, place, and material transformation. Each manufacturer or distributor has some subset of the supply chain that it must manage and run profitably and efficiently to survive and grow. Decisions about how to plan a company's supply chain operations can be operational, tactical, or strategic. Strategic decisions are the most far-reaching and difficult to make. These decisions are characterized by complexity, interdependence, and uncertainty. Simulation and optimization modeling techniques are used to help make supply chain strategic decisions. The four step methodology is a proposed approach to supply chain strategic planning that attempts to leverage the strength of multiple modeling techniques. Each step solves a different part of the master planning problem, using either optimization, simulation, or simulation-optimization. By using complementary modeling approaches together in the Four Step Methodology, the supply chain planner's activities and decisions can be greatly improved.
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  W. Swain Ottman
Angela C. Ford
Gregory R. Reinhardt
United Parcel Service
1400 North Hurstbourne Parkway
Louisville, KY 40223, U.S.A.
The Louisville International Airport arrives and departs over 200 flights on a daily basis for United Parcel Service (UPS). The number of arrivals and departures continues to grow with the expansion of the airport and UPS.. A simulation model was developed to analyze the daily taxi and takeoff operation of UPS aircraft. Inputs to the model include aircraft schedules, flight patterns and runway information. Customized outputs include aircraft departure statistics for each flight and runway utilization. The model assists planners in developing aircraft departure schedules that minimize taxi and ramp delay times.
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Michel R. Gatersleben
Amsterdam Airport Schiphol,
Logistics Competence Centre (LCC)
P.O. Box 7501
Simon W. van der Weij
Incontrol Business Engineers
Planetenbaan 21
As human behavior is often thought to be hard to define in models, simulations of processes with people involved are less common than industrial simulations. Nevertheless simulation has been very valuable in passenger logistics to study bottlenecks and test potential solutions. This paper describes a project concerning the analysis and redesign of passenger handling at an airport, in which dynamic modeling played an important role.
Simulation has been applied here to get insights in the relations between the distinguished processes, the presence of bottlenecks and their causes. With the simulation models future situations were represented, through which long-term expectations can be posted. In this way critical aspects in the passenger flow through the airport terminal have been explored and studied. All potential bottlenecks have to be suppressed by apt arrangements. These can consist of an expansion of the availability of resources or floor space, but many times improving the processes can be a more effective or more efficient solution. Several supposed measurements have been tested in a quantitative way, to examine whether they fulfill the expectations, are robust and do not create new problems.
The overview of bottlenecks and the comparison of measurements formed the required results of the simulation project. However, some other effects of the study turned out to be just as useful. As detailed simulation studies require exact descriptions of processes and representative data, a large amount of information had to be collected and laid down. Process control and management will take advantage of it. Furthermore the modeling of he complete chain of processes supplied an increased insight in the dynamics and the intra-organizational relations. So in the future sub-optimal solutions can be avoided and communication improved.
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  Bruce Schumacher
Delta Air Lines
Dept. 487
1775 Aviation Blvd.
Atlanta, GA 30320-6001, U.S.A.
Delta Air Lines is the first and only airline to carry over 100 million passengers in a year, carrying over 105,000,000 passengers in 1998. To provide service to this number of passengers, Delta operates a "hub and spoke" flight system. In the hub and spoke system, certain key airports, or hubs, are designated as the origination point of a large number of flights, thereby allowing a passenger departing from a hub airport almost unlimited flexibility in terms of direct flight destinations. A change in the operation of the runways in one of Delta's hub airports was planned, and Delta management wanted to determine the effect on the dependable operation of the current and future flight schedules.
Flight schedule dependability can be defined as the reliable, consistent, and timely operation of a published flight schedule. For several reasons, schedule dependability is absolutely critical to the successful operation of an airline. The airline industry is extremely competitive, and schedule dependability is an important benchmark that differentiates competing airlines in the eyes of many customers. Also, schedule dependability is critical to the profitability of an airline because of the high cost of an unreliable operation. These costs include repositioning aircraft, accommodating inconvenienced passengers, and adjusting pilot and flight attendant schedules.
The purpose of this paper is to present two simulation models used to evaluate proposed flight schedules and to quantify the effect of changes in conditions at a major hub airport on the proposed schedule.
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  Beth C. Kulick
James T. Sawyer
Automation Associates, Inc.
512 Via de la Valle Suite 209
Solana Beach, CA 92024-2714
SIMCAP (Simulation-based Capacity Analysis Plat-form) is a simulation-based software tool designed to support analysis of intermodal terminal operation, specifically with respect to track capacity and yard capacity. The application was designed with a modular, extensible software architecture with an emphasis on capturing the primary complexities that exist in an actual intermodal terminal. SIMCAP is not just a simulation model, but a modeling system that comprises several interacting software components. Each component represents a functional aspect of facility operations allowing for future implementations of terminals with different equipment, layout, and procedures to be more readily adapted without major coding revisions.
The ability to analyze terminal designs with alternate track layouts, equipment configurations, and varying demand requirements was of paramount importance when designing and developing SIMCAP. The first implementation of the SIMCAP paradigm was developed for Burlington Northern Santa Fe railroad; it was successfully used to analyze capacity during a peak period at an existing intermodal terminal. It is planned to further use the tool to compare terminal performance as proposed infrastructure changes are made.
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  Agostino G. Bruzzone
Pietro Giribone
Roberto Revetria
DIP - University of Genova
Via Opera Pia 15, 16145 Genova, ITALY
This paper outlines the evolution of container terminal requirements for simulation and the potential of new advanced techniques in the integration with these aspects; the authors present application examples and experimental results that maximized the impact of these new concepts in real complex port realities.
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  Reza Naghshineh-pour
Nicole Williams
Bala Ram
Department of Industrial Engineering
North Carolina A&T State University
Greensboro, NC 27411, U.S.A.
To enable longer space missions, systems for production of food in space will be necessary. The Autonomous Life Support System (ALSS) program of NASA is an on-going research effort in this direction. This research uses intelligent agents to relieve the crew of substantial efforts relating to the food production tasks. In this paper, we propose a Contract Net Protocol approach to schedule transportation activities within this environment. A discrete-event simulation model using QUEST software (by Deneb Robotics, Inc.) is used to represent the flow of the transportation traffic within the system.
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  William R. Lesyna
E. I. DuPont & Co., Inc.
DuPont Engineering Technology
1007 Market Street
Wilmington, DE 19898, U.S.A.
DuPont has many products that use rail cars in various portions of their supply chains. Often these cars are used to deliver final products to a variety of customers at different geographical locations. In many cases it is difficult to optimally size these fleets, since the underlying system is complex, dynamic, and involves random variables.
This paper describes how DuPont has used discrete-event simulation ("DES") to optimally size an industrial rail car fleet used to deliver final products to customers. It explains why it is important to DuPont to optimize the size of our rail car fleets; how such fleets are sized without DES; the value of DES in modeling one particular rail car system; and some of the lessons from building such DES models.
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Michael Norman
Deron Tinsley
AutoSimulations, Inc.
655 Medical Drive
Bountiful, UT 84010, U.S.A.
Jerry Barksdale
Otto Wiersholm
Dominion Semiconductor
9600 Godwin Drive
Manassas, VA 20110, U.S.A.
Philip Campbell
Edward MacNair
IBM Microelectronics Div.
Mail Stop - 56A
1580 Hopewell Jct., NY 12533, U.S.A.
AutoSimulations has developed and applied a new method of integrating separate models of manufacturing process and material handling systems that exploits the strengths of two different products to provide users with maximum productivity and flexibility. As applied to semiconductor wafer fabrication facilities in the examples presented here, this approach replaces the traditional method of building a single large, complex model of the entire scope of operations. Two case studies illustrate the technique and demonstrate the benefits of this new modeling architecture.
IBM recently contracted with AutoSimulations to upgrade an existing model of their prototype 300mm wafer fabrication facility. The existing model was developed in 1997 using the AutoSched™ application, a long-time manufacturing system modeling product from AutoSimulations. It incorporated various material handling systems (different configurations of overhead monorail layouts and use of operators) and manufacturing processes within one model - the standard practice for modeling wafer fabrication facilities with the intent of understanding material handling requirements and process requirements for varying order demand.
In 1998, Dominion Semiconductor, a subsidiary of IBM and Toshiba, contracted with AutoSimulations to develop a coordinated tool set to meet a diverse set of requirements to support their fabrication of 200mm wafers. The manufacturing support group needed assistance in planning process capacity, in planning future staffing requirements, and in analysis of cost reduction initiatives and production scheduling, including lot start and dispatch policies. The automated material handling system (AMHS) support group wanted a dynamic and graphical means of justifying new equipment and analyzing potential system modifications, as well as a tool to assist with other planning and daily system support activities.
AutoSimulations' solution for both projects was to integrate a detailed model of the automated material handling system, developed in the AutoMod™ software, with a manufacturing model developed in the AutoSched AP™ software, using a new product call the Model Communications Module™ (MCM). Material handling moves requested via messages by the AP model are executed in the AutoMod model. Other inter-model messaging coordinates processes in each model dependent on equipment availability or other material handling system conditions. Each model may also be run independently to facilitate specific uses by both groups.
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Marelys L. Garcia
Lockwood Greene Consulting
250 Williams Street
INFORUM Suite 2350
Atlanta, GA 30303 USA
Martha A. Centeno
Gabriela Peñaloza
Department of Industrial and Systems Engineering
Florida International University
Miami, Florida 33199 USA
On-time delivery of the paper is critical in the newspaper industry since it is directly related to the quality of service; therefore, it enhances or damages sales. This study was focused on determining the means to meet required delivery times, and in identifying ways to improve it, so that there is a lower probability of failure. A simulation model was built to model the paper printing, packaging, and distribution processes. The results yielded a press schedule and warehouse assignments that provided a 13% improvement on delivery time. This improvement results in a 97% on time delivery of the paper.
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Nico M. van Dijk
Mark D. Hermans
Maurice J.G. Teunisse
Incontrol Business Engineers
Planetenbaan 21
Henk Schuurman
Ministry of Transport, Public Works and Watermanagement
Transport Research Centre (AVV)
P.O. Box 1031
3000 BA Rotterdam, THE NETHERLANDS
This paper describes how a combined queueing and simulation study was successfully executed for the design of a toll plaza. The objectives of the study were twofold:
  • to configure the types of toll booths with multiple payment functionalities (cash, credit cards, and electronic payment).
  • to determine the number of toll booths for each type.
The model was also used to validate the spacing, safety, and accessibility of the toll plaza.
A hybrid approach of simulation and queueing theory proved to be a powerful method in analyzing the queueing processes of the toll plaza. This approach combined the insights from queueing theory with the practical applicability of simulation. Queueing theory provided the conceptual framework and limited the number of variants to be examined, while simulation was used to compare and evaluate the variants.
The study showed that fewer toll booths were needed when different payment systems were separated, as a combination of different payment systems at one toll booth would substantially enlarge the variability of service times. This variability appeared to dominate the 'inefficiency' of separate toll booths which may seem counterintuitive. Consequently, the initial design had to be completely redesigned.
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Key Factors in Road-Rail Mode Choice in India: Applying the Logistics Cost Approach  
Peter D. Cook
GIS/Trans, Ltd.
8555 16th St., Suite 700
Silver Spring, MD 20910 U.S.A.
Sanjay Das
Ministry of Agriculture
New Delhi, India
Andreas Aeppli
A&L Associates
101 Rogers St., Suite 403
Cambridge, MA 02142 U.S.A
Dr. Carl Martland
Department of Civil Engineering
77 Massachusetts Ave.
Massachusetts Institute of Technology
Cambridge, MA 02139 U.S.A.
There have been major changes in the share of road and rail traffic in India as the economy and the population has grown and become more urbanized. This paper summarizes the key factors for mode choice in freight transport that were found in India in a recent survey based on the Logistics Cost Model of shipper behavior. Both the relative importance of these factors and customer rating of satisfaction is presented.
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  Paul Martin
Senior Simulation Engineer
Comreco Rail Ltd
St Marys Court
39 Blossom Street
YO24 1AQ
Simulation provides a valuable tool in both the design of new infrastructure coupled with assisting in the process of translating a railways business aspiration into a technical specification.
The simulation system can be used in many forms:

As a single train run to assess traction performance over a given infrastructure or assumptions of the physical characteristics of a new line.
To assess a range of signalling systems in order to identify the optimum solution to meet a service aspiration.
Evaluation of proposed timetables and the interaction between the trains at a complex junction or in major terminals.

This paper seeks to demonstrate the varying levels of simulation and their key role in the support of railway projects and the benefits from integrating simulation tools.
Topics to be covered include: -

Single Train Simulation
Project Development
Multi Train Simulation
System Integration

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David K. Chin
Aerospace & Information Systems
TRW in Washington, DC
Fran Melone
Investment Analysis & Operations Research
FAA in Washington, DC
There is a general consensus between the Federal Aviation Administration (FAA) and the aviation industry on the enormous potential for time and resource savings associated with future flights that are subject to less Air Traffic Control (ATC) restrictions. In support of the Free Flight paradigm, the FAA is investing billions of dollars to introduce new Communication, Surveillance, Navigation/Air Traffic Management (CNS/ATM) technologies into the National Airspace System (NAS) and has outlined an architecture plan to modernize it. It is expected that with the deployment of these new capabilities, users will benefit from better services, such as greater wind-optimized cruise trajectories and altitudes and more efficient surface traffic operations.
This paper describes the results of our Free Flight study, in which we used several simulation models and data base tools to evaluate fuel savings and aircraft emission reductions that are associated with the planned implementation of the capabilities outlined in the NAS architecture. Specifically, this paper will focus on the approach and simulation tools that were used to analyze the fuel and emission conservation metrics by aircraft type and phase of flight.
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  Todd M Johnson
AutoSimulations, Inc.
655 Medical Drive
Bountiful, UT 84010
This paper presents a flexible, rental car lot simulation model. This data-driven model serves as a template that can be used to easily test configurations and options used in the real system. The advantages of this simulation model as an analysis tool and the knowledge Avis learned as a result of simulation analysis are presented.
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Michael Carter
Air Force Studies and Analyses Agency
1570 Air Force Pentagon
Washington, DC 20330-1570
Mark R. Grabau
Air Force Studies and Analyses Agency
1570 Air Force Pentagon
Washington, DC 20330-1570
Michael Kram
Tanker Airlift Control Center
402 Scott Drive Unit 2K1
Scott Air Force Base, IL 62225-5503
The United States Air Force's Air Mobility Command operates airlift missions that service the United States Navy's Pacific Fleet in the Indian Ocean. All of these missions travel through Singapore's airport, which has very restrictive operating hours. This paper discusses the use of simulation to assess the cycle time impacts of changing Singapore and Fujairah's operating hours and aircraft ground times.
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  Charles H. White
Bing W. Tsai
DuPont Engineering Technology
DuPont Company
Wilmington DE, 19898, USA
Production Operations can usefully be partitioned into Discrete Manufacturing and Processing Operations. Discrete Manufacturing plants produce products such as automobiles, airplanes, refrigerators, toasters, computers, and such 'discrete' products often have quite large work-forces relative to plants such as refineries, distillers, and chemical plants. Processing Operations systems produce 'stuff' such as gasoline, paint, beer, ice cream, and chemicals. Processing Operations can then be classified as 'continuous', 'batch', and 'hybrid' (batch and continuous). Many of Process Operations systems are both capital intensive and use relatively low manpower. Process systems often have a lot of expensive equipment; refineries and chemical plants have a lot of large expensive equipment and control systems. Also relative to most manufacturing systems Process plants have few operators (there are some 'field operators' and automated control rooms run by a relatively small number of operators and engineers). 'Continuity of Operations' is very important in such plants both for economic reasons and technical reasons; specifically, shutdowns interrupt the continuous flow of production and can cause expensive and time-consuming shut-down and start-up situations.
Another factor that can be an important difference is that of co-products, by-products, and waste streams. In many petro-chemical plants there are natural ratios (think of these as 'recipes') of input streams and output streams that can be controlled only over a narrow range. For instance in an oil refinery the crude oil is 'cracked' into gasoline, kerosene, and several other products and this can be controlled only over a narrow range. The point is that some kerosene will always be produced when producing gasoline. In many chemical systems producing the main product results also in making such co-products and by-products (these really differ only in the relative value associated with these products) as well as waste. Waste is essentially a by-product with a negative value; we need to spend money to dispose of it. Yields are associated with 'how much good stuff' we get relative to the input feed streams. In manufacturing operations this is the pounds of good product per pound of input materials. In typical metalworking operations this might be in the 70-95% range. In chemicals production the yields (recall this is the ratio of good product to the input feed materials) can be very low. In fact in this paper we will be discussing a situation where the production process is a solvent based operation where the yields can be (based on the above definition of yield) in the 5% range. The reason for this is that the ratio of solvent to product ranges from 1:1 up to 20:1. This can result in some unusual logistical problems.
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  Tony Gossard
Nancy Brown
Steve Powers
David Crippen
Kelley Logistics Support Systems, Incorporated
398 East Dayton-Yellow Springs Road
Fairborn, Ohio 45324, United States of America
The Scalable Integration Model for Objective Resource Capability Evaluations (SIM-FORCE) provides Air Force decision-makers with a tool to evaluate potential actions and analyze expected results. The model evaluates the impact of schedule changes or resource availability on mission completion. It is a desktop tool that will support a wide variety of critical day to day decisions facing unit level managers. The simulation engine is built using Arena®. The simulation models aircraft launch processes, system breaks or failures and the resources required to support the launch and repair of broke items. The processes modeled are similar to those used by most types of maintenance, regardless of the type of equipment being maintained, including aircraft, industrial presses, recreational vehicles and long haul trucks. The modeled maintenance process is designed to transition SIM-FORCE into a future generic tool that supports commercial as well as military maintenance applications.
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Soemon Takakuwa
School of Economics and Business Administration
Nagoya University
Furo-cho, Chikusa-ku, Nagoya-shi, Aichi, 464 JAPAN
Tsukasa Fujii
Aichi Prefectural Police Academy
Aichi Prefecturral Police Headquarters
Hazama-cho 703, Kasugai-shi, Aichi, 486 JAPAN
A method of modeling transshipment-inventory systems is proposed in an attempt to describe the systems flexibly in which a lot of kinds of items are ordered to transport and transship, transported, stored, and delivered to the customers. The system consists of a number of supply, transshipment and demand nodes. However, the problem considered in this study is totally different from the traditional transshipment problem in terms of linear programming. Firstly, any number of different kinds of items can be treated for analysis. Secondly, any size of transportation trucks can be specified to transport items for any number of the two-node combinations. In other words, the capacity of the transportation truck is to be specified in building a simulation model. In addition, any number of supply, transshipment and demand nodes can be specified in a simulation model. Thirdly, the order by a demand node is made toward the associated transshipment node, based on the inventory policy at the demand node, and the so-called the "pull system" is adopted in the demand-supply environment.
An efficient module-based modeling method is proposed to generate simulation models for the above-mentioned transshipment-inventory systems. The proposed method is applied to the actual system. It is found that the time to build simulation models could be drastically reduced. Furthermore, the proposed method is found to be both practical and powerful.
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Distributed Supply Chain Simulation in a DEVS/CORBA Execution Environment  
Bernard P. Zeigler
AI and Simulation Group
Department of Electrical and Computer Engineering
University of Arizona
Tucson, Arizona
  Doohwan Kim
Stephen J. Buckley

IBM T. J. Watson Research Center
P. O. Box 218
Yorktown Heights, NY 10598
The emerging electronic commerce and rapidly changing business environments place strong requirements on a next-generation supply-chain analyzer to simulate the flow of goods through the entire supply chain in a timely manner. Such requirements include scalable and efficient model execution and support for flexible future extensibility based on an open industry standard. This paper presents design considerations for a supply chain modeling and simulation environment to execute in a parallel and distributed manner on a DEVS/CORBA run time infrastructure. We recall that DEVS (Discrete Event System Specification) is a sound formal modeling and simulation framework based on generic dynamic systems concepts that can integrate into a parallel and distributed run time infrastructure. CORBA (Common Object Request Broker Architecture) is an open standard that is rapidly gaining universal business acceptance. It can be employed as middleware to support a heterogeneous, network-centric, distributed computing environment that includes modeling and simulation as well as other business objects. Implementing a distributed supply chain simulator in a DEVS/CORBA execution environment not only may significantly improve execution speed but also may provide advanced supply chain model development capability based on the DEVS modeling and simulation framework.
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  Russell E. King
Kara Moon
Department of Industrial Engineering
North Carolina State University
Raleigh, NC 29695-7906
In this paper we document a case study based upon an on-going analysis for a U.S. fiber/fabric manufacturer who is expanding its operations vertically to include cut and sew operations in Mexico. We will refer to this Vertically Integrated Manufacturer as VIM in this paper. While some of the data have been changed to protect the sources, the story and results themselves are unchanged. More detail on this case can be found in Moon (1999).
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How i2 Integrates Simulation in supply Chain Management  
  Jeremy Padmos
Bill Hubbard
Tom Duczmal
Slim Saidi
i2 Technologies
This paper will set out, at a high level, the methods in which i2 solutions will enable value in the 21st century enterprise. With regards to the purposes of the Winter Simulation Conference, we will show how simulation fits within our solution set and how we have extended the principles of simulation
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