2009 Simulation Workshop

2009 Simulation Workshop

2009 INFORMS Simulation Society Research Workshop

Simulation: At the Interface of Modeling and Analysis

June 25-27, 2009 at University of Warwick, Coventry, U.K.

The 2009 INFORMS Simulation Society Research Workshop is a forum for researchers to exchange ideas and results and to discuss new developments in the simulation of stochastic process and discrete-event systems. The goal of the workshop is to bring together leading researchers working in a variety of theoretical, empirical, application and implementation domains in order to reflect on the central theme.

The workshop is the second of its kind. The first workshop was held July 5-7, 2007, at the Fontainebleau, France, campus of INSEAD. The theme of the first Workshop was "Simulation for better decisions in an uncertain world". In this second workshop, we build on the success of the first to further advance the science of simulation relative to decision making.

Advances in Modeling and Simulation of Nonstationary Arrival Processes
Michael E. Kuhl (Rochester Institute of Technology) and James R. Wilson (North Carolina State University)

Modeling and Simulating Non-Poisson Arrival Processes to Facilitate Analysis
Barry L. Nelson (Northwestern University) and Ira Gerhardt (Manhattan College)
pdf paper8-10 

How Modeling Limits Analysis - The Long Way from Distributed Simulation to Reality
Peter Lendermann (D-SIMLAB Technologies)
pdf paper11-14 

Embedded Ad Hoc Distributed Simulation for Transportation System Monitoring and Control
Michael Hunter (Georgia Institute of Technology), Jason Sirichoke (Hewlett-Packard Company), Richard Fujimoto (Georgia Institute of Technology) and Ya-Lin Huang (Georgia Institute of Technology)
pdf paper15-19 

Analysis of Output Data in Distributed Simulation
B. Vinod Kumar Reddy and Jayendran Venkateswaran (Indian Institute of Technology - Bombay)
pdf paper20-24 

Non-standard Statistical Metamodels
Russell Cheng (University of Southampton)
pdf paper25-29 

Application of Monte Carlo Sampling to Assess Experimental Designs in Developmental Test
Derek A. Leggio (United States Strategic Command) and Raymond R. Hill (Air Force Institute of Technology)
pdf paper30-36 

Comparison of Simulation Output Series using Bootstrapping
Christine S.M. Currie and Lanting Lu (University of Southampton)
pdf paper37-40 

A Web Based Simulation Application
Cathal Heavey (University of Limerick), James Byrne (University of Limerick), Paul Liston (University of Limerick) and P.J. Byrne (Dublin City University)
pdf paper41-45 

Modeling and Analyzing Cargo Screening Processes: A Project Outline
Peer-Olaf Siebers (Nottingham University), Uwe Aickelin (Nottingham University), David Menachof (City University London), Galina ShermanCity (University London) and Peter Zimmerman (King's College London)
pdf paper46-49 

Robust Simulation-Optimization Methodology
Jack P.C. Kleijnen (Tilburg University), Gabriella Dellino (University of Siena), and Carlo Meloni (Polytechnic of Bari)
pdf paper50-54 

Monte Carlo Inference on Sample-Path Roots
Raghu Pasupathy (Virginia Tech)
pdf paper55-58 

A Simulation Based and an Analytic Modeling Approach to Calculate an Appropriate Number of FOUPs in Wafer Fabs
Lars Mönch (University of Hagen), Jens Zimmermann (University of Hagen) , John W. Fowler (Arizona State University) and Scott J. Mason (University of Arkansas)
pdf paper59-63 

A Virtual Power System Testbed for Cyber-Security Decision Support
David M. Nicol (University of Illinois at Urbana-Champaign), Charles M. Davis (PowerWorld Corporation) and Thomas Overbye (University of Illinois at Urbana-Champaign)
pdf paper64-68 

The Key to Promoting Interaction between Simulation Modeling and Analysis Research: Practice
Douglas J. Morrice (The University of Texas at Austin)
pdf paper69-72 

Data Collection Budget Allocation for Stochastic Data Envelopment Analysis
Loo Hay Lee, Wai Peng Wong and Wikrom Jaruphongsa (National University of Singapore)
pdf paper73-76 

Automating Discrete Event Simulation Output Analysis - Automatic Estimation of Number of Replications, Warm-up Period and Run Length
Kathryn Hoad, Stewart Robinson and Ruth Davies (The University of Warwick)
pdf paper77-81 

Modeling and Analysis of the Trade-offs in Surgical Suite Performance Measures
Serhat Gul (Arizona State University), John W. Fowler (Arizona State University) and Brian T. Denton (North Carolina State University)
pdf paper82-86 

A Proposed Approach for Modeling Care Pathways for Infrastructure Design Briefing
Amna Shibeika and Colin Gray (University of Reading)
pdf paper87-91 

The Problem of the Initial Transient (Again), or Why MSER Works
K. Preston White, Jr. (University of Virginia) and Stewart Robinson (University of Warwick)
pdf paper92-97 

Dynamic Learning in Human Decision Behavior for Evacuation Scenarios under BDI Framework
Seungho Lee and Young-Jun Son (The University of Arizona)
pdf paper98-102 

Investigating Output Accuracy for a Discrete Event Simulation Model and an Agent Based Simulation Model
Mazlina Abdul Majid, Uwe Aickelin and Peer-Olaf Siebers (Nottingham University)
pdf paper103-107 

Determining the Range of Predictions for Calibrated Agent-based Simulation Models
DongFang Shi and Roger J. Brooks (Lancaster University Management School)
pdf paper108-112 

Why Modeling Still Matters in Discrete Simulation
Michael Pidd (Lancaster University Management School)
pdf paper113-116 

A General SYSML Model for Discrete Processes in Production Systems
Oliver Schönherr and Oliver Rose (Dresden University of Technology)
pdf paper117-120 

Database Meets Simulation: Tools and Techniques
Peter J. Haas (IBM Almaden Research Center) and Christopher Jermaine (Rice University)
pdf paper121-126 

What Contributes to the Quality of Simulation Results?
Jan Himmelspach and Adelinde M. Uhrmacher (University of Rostock)
pdf paper127-131