Modeling a simulation system requires a great deal of customization. At first sight no system seems to resemble exactly another system and every time a new model has to be designed the modeler has to start from scratch. The present simulation languages provide the modeler with powerful tools that greatly facilitate building models (modules for arrivals or servers, etc.). Yet, also with these to...

This paper describes a discrete event simulation study of an emergency department at Dr. Georges-L. Dumont Hospital in Moncton (Canada). The objective of the study was to reduce patient waiting times and to improve overall service delivery and system throughput. As patient waiting times are linked to resource availability, a number of alternatives were designed based on adding resource scenario...

Intel has recently developed lot routing tools that can theoretically minimize local and overall lot movement. These developments were required to maximize the flexibility of existing AMHS and minimize the time needed to retrieve lots for processing. In order to gain insight of how these lot routing rules impact manufacturing, and how they should be configured, Intel uses two different analysis...

This tutorial will present a methodology for modeling of human performance using multiple resource theory within a discrete event simulation. Participants will gain an understanding of why modeling human performance can be important and how workload models can be used to support system design. This presentation will include the theoretical background as well as detailed the techniques for model...

Cross-docking is a distribution system where products transported from warehouses to destinations are unloaded temporarily at intermediate facilities, and loaded onto outbound trucks to be shipped to their final destination. The complexity of cross-docking operations has been considered a problem of great interest to researchers and practitioners in the areas of Scheduling, Optimization, Supply...

Discrete event simulation and agent-based modeling are increasingly recognized as critical for diagnosing and solving process issues in complex systems. Introduction to Discrete Event Simulation and Agent-based Modeling covers the techniques needed for success in all phases of simulation projects. These include: Definition – The reader will learn how to plan a project and communicate using a ch...

The resource levels required for operation and support of reusable launch vehicles are typically defined through discrete event simulation modeling. Minimizing these resources constitutes an optimization problem involving discrete variables and simulation. Conventional approaches to solve such optimization problems involving integer valued decision variables are the pattern search and statistic...

Infinitesimal Perturbation Analysis (IPA) estimators of the response gradient for a discrete event stochastic simulation are typically developed within the framework of Generalized semi-Markov processes (GSMPs). Unfortunately, while mathematically rigorous, GSMPs are not particularly useful for modeling real systems. In this paper we describe a procedure that allows IPA gradient estimation to b...