WSC 2001 Final Abstracts

General Applications Track

Tuesday 10:30:00 AM 12:00:00 PM
Complex and Interconnected Systems

Chair: Thomas Wiedemann (Technical University of Berlin)

Optimistic Parallel Simulation of a Large-Scale View Storage System
Garrett Yaun, Christopher D. Carothers, Sibel Adali, and David Spooner (Rensselaer Polytechnic Institute)

In this paper we present the design and implementation of a complex view storage system model. Here, a hierarchy of view storage servers are connected to an array of client-side local disks. The term view refers to the output or result of a query made on the part of an application that is executing on a client machine. This model has been designed for execution with an optimistic simulation engine. One of the primary drawbacks of this parallel synchronization mechanism has been high overheads due to state-saving. We attack this problem by implementing the model using reverse computation. In our performance study of this application, we find that speedups range from 1.5 to over 5 on 4 processors. Super-linear speedups are attributed to a slow memory subsystem and the increased availability of level-1 and level-2 cache when moving to a larger number of processors.

Towards COTS Distributed Simulation Using GRIDS
Simon J.E. Taylor, Rajeev Sudra, and Tharumasegaram Janahan (Brunel University), Gary Tan (National University of Singapore) and John Ladbrook (Ford Motor Company)

This paper reports on continuing work that concerns research into the development of a commercial off the shelf (COTS) distributed simulation environment (federation) using the Generic Runtime Infrastructure for Distributed Simulation to support the interoperation of simulation packages such as Arena, Extend, Simul8, Taylor, Witness, etc. The main aim of this work is to provide the industry with a business benefit from distributed simulation by making it possible to reuse previously developed models in order to address different problems within enterprises or between enterprises (supply chains) that could not otherwise be addressed due to barriers of cost and time. The approach emphasises transparency and minimal intervention with the simulation modeller. Two cases are presented: a distributed supply chain simulation (federation), and an example from the automotive industry.

Simulation of Rare Events in Transportation Systems
Lori M. Kaufman and Ted C. Giras (University of Virginia)

Prior to the deployment of any new or replacement component within a transportation system, it should be demonstrated that the modified system meets or exceeds the safety requirements of the original system. Since the occurrence of a mishap in such a system is a rare event, it is neither cost nor time effective to build and to test a prototype in an actual system prior to deployment. The Axiomatic Safety-Critical Assessment Process (ASCAP) is a simulation methodology that models the complete system and analyzes the effects of equipment changes. By carefully constraining the amount of the overall system state space required for analyses, it probabilistically determines the sequence of events that lead to mishaps. ASCAP is applicable to any transportation system that is governed by a well-defined operational environment.

Tuesday 3:30:00 PM 5:00:00 PM
Healthcare I

Chair: Tillal Eldabi (Brunel University)

A Discrete-Event Simulation Application for Clinics Serving the Poor
Christos Alexopoulos and David Goldsman (Georgia Tech) and John Fontanesi, Mark Sawyer, Michelle De Guire, David Kopald, and Kathy Holcomb (University of California, San Diego)

Healthcare management operates in an environment of aggressive pricing, tough competition, and rapidly changing guidelines. Computer simulation models are increasingly used by large healthcare institutions to meet these challenges. However, small healthcare facilities serving the poor are equally in need of meeting these challenges but lack the finances and personnel required to develop and implement their own simulation solutions. An academic medical center, healthcare facilities that serve the poor, and the local public health department formed a unique partnership to create low-cost tools to meet these challenges. This article describes the creation of a low-cost, generic, discrete-event simulation model populated by a workflow observation Excel spreadsheet that can be completed by clinic staff themselves, thus “customizing” the simulation model for their own purposes. This initial model focuses on childhood immunization delivery services; the intent is to develop a tool flexible enough to serve other health services delivery needs as well.

A Simulation Study of the Labor and Delivery Rooms at JMH
Martha A. Centeno, Marsha A. Lee, and Elizabeth Lopez (Florida International University) and Helida R. Fernandez, Manuel Carrillo, and Tom Ogazon (Jackson Memorial Hospital)

This paper presents a simulation model of the operations in the Labor and Delivery Rooms at Jackson Memorial Hospital. A thorough analysis of the contents of hospital’s databases revealed that although there is a significant amount of data, some of it is not usable. Nonetheless, with the available data, it was possible to establish relatively good inputs for the simulation model. Furthermore, it was possible to do a correlation analysis to determine which factors affect the procedure service times in the OR and Recovery areas. The simulation model has yielded results to improve doctor scheduling and better staffing levels.

The Use of Simulation for Process Improvement at an Ambulatory Surgery Center
Francisco J. Ramis, Jorge L. Palma, and Felipe F. Baesler (Universidad del BioBio)

This work has for objective building a simulation model to evaluate different alternatives of operation of a projected center for ambulatory surgery. For the construction of the model a group of pathologies was selected and real data was taken from statistics of surgeries from a clinical hospital. The information was supplemented by the opinion of medical surgeons and expert anesthesiologists. Similarly, the model was validated by means of the opinion of experts and implemented with the Arena simulation software. Different configurations of operating conditions were studied. It is concluded that the maximum throughput of daily surgeries is achieved, 10 in total, dedicating two beds to preparation of patient, five beds to the transitory hospitalization and using an LPT scheduling rule in the operating rooms, i.e., the heaviest surgeries first.

Wednesday 8:30:00 AM 10:00:00 AM
Healthcare II

Chair: Francisco Ramis (Universidad del Bio-Bio)

Multi-Objective Simulation Optimization for a Cancer Treatment Center
Felipe F. Baesler (Universidad del BioBio) and José A. Sepúlveda (University of Central Florida)

This paper presents a case study application of a cancer treatment center facility. A simulation model was created and integrated to a multi-objective optimization heuristic developed by the authors with the purpose of finding the best combination of control variables that optimize the performance of four different objectives related to the system. The results obtained show that the implementation of the proposed solution could improve the four objectives in comparison to the existing solution.

A Proposed Approach for Modeling Healthcare Systems for Understanding
Tillal Eldabi and Ray J. Paul (Brunel University)

The use of simulation in healthcare area is not widely spread when compared with other areas. This paper suggests that traditional approaches to modeling may not fully utilize simulation for tackling healthcare problems. Healthcare systems are often complex with multiple decision makers. A modeling approach is proposed in this paper to enhance stakeholders’ understanding and intercommunications. The structure of this approach is participative including the stakeholders. The behavior of the approach is iterative rather than step-based. An example is given showing how this approach is used for facilitating the modeling process. It is found that involving stakeholders throughout the modeling process helps them understand their problem coupled with more appreciation to findings from the model. This process is also found useful in enhancing stakeholders’ intercommunication.

Using Monte Carlo Simulation to Assess the Value of Combination Vaccines for Pediatric Immunization
Sheldon H. Jacobson (University of Illinois), Edward C. Sewell (Southern Illinois University Edwardsville) and Bruce G. Weniger (Centers for Disease Control and Prevention)

Research by vaccine manufacturers has resulted in the development of new vaccines that protect against a number of diseases. This has created a dilemma for how to introduce such new vaccines into an already crowded Recommended Childhood Immunization Schedule and prompted the development of vaccine products that combine several individual vaccines into a single injection. Such combination vaccines permit new vaccines to be inserted into the immunization schedule without exposing children to an unacceptable number of injections during a single clinic visit. This paper describes a Monte Carlo simulation with an integer programming model to assess and quantify the distributions around inclusion prices which reflect the economic premium of these new combinations. Each new vaccine competed against existing vaccines for six childhood diseases (hepatitis B, diphtheria, tetanus, pertussis, Haemophilus influenzae type b, and polio) at their March 2000 Federal contract discount prices.

Wednesday 10:30:00 AM 12:00:00 PM
Simulation Practice

Chair: Boonserm Kulvatunyou (Penn State University)

Key Enablers in the Development of Simulation
Stephen P. Murphy and Terrence D. Perera (Sheffield Hallam University)

The awareness of simulation technologies within the UK is relatively small when compared with the USA. Subsequently several large US companies have been able to overcome the difficulties in adopting new technology into their business and introduce simulation. This paper investigates the problems encountered and the practices helping to successfully implement simulation into a company environment. Details of a major survey conducted to determine the approaches taken by large automotive and aerospace companies within these two countries are outlined. The survey highlighted differences in the development of simulation within twelve large companies, the extent of the difference and the reasons why these differences exist.

Call Center Scheduling Technology Evaluation Using Simulation
Sandeep Gulati and Scott A. Malcolm (University of Delaware)

Telemarketers, direct marketing agencies, collection agencies and others whose primary means of customer contact is via the telephone invest considerable sums of money to make the calling operation efficient and productive. Investments are required in human resources, infrastructure and technology. Having invested the dollars, businesses want to ensure that value is maximized. Call scheduling algorithms provide an efficient method to maximize customer contact. However, management at a large, national credit card bank was not convinced that the software used to schedule calls was providing an adequate level of service. Simulation studies showed that management was justified in this assumption. The study also revealed that process improvement opportunities exist, which if implemented would likely produce the desired performance improvements.

Choosing Among Seven Bases
Stuart Gittlitz (S & G Simulations)

In this paper, the selection of a BASE Case was every bit as important as the simulation itself. The production team had been familiar with simulations and had used their results on previous projects. The team was concerned with the design of additional capacity for a current production line along with their ability to gain approval for the proposed project. They knew that simulation could be the basis for their decisions. But first they had to ask the right questions. This production line, at a major food manufacturer, had been simulated and reviewed. Since the original simulation, it was noted that the Cartoner speed and overall efficiency had been stated at too high a level. New simulations were required to support the project. While 88% efficiency had been used in the prior simulation, the historical efficiency was only at 60%. But that level of productivity would be considered unacceptable as a BASE to request the purchase of additional equipment.

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