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Simulation Modeling and Analysis

TLDR
The text is designed for a one-term or two-quarter course in simulation offered in departments of industrial engineering, business, computer science and operations research.
Abstract
From the Publisher: This second edition of Simulation Modeling and Analysis includes a chapter on "Simulation in Manufacturing Systems" and examples. The text is designed for a one-term or two-quarter course in simulation offered in departments of industrial engineering,business,computer science and operations research.

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Book

Simulation: The Practice of Model Development and Use

TL;DR: This nontechnical textbook is focused towards the needs of business, engineering and computer science students and aims to improve efficiency and effectiveness in simulation modelling.
Journal ArticleDOI

Analyzing the benefits of lean manufacturing and value stream mapping via simulation: A process sector case study

TL;DR: A case where lean principles were adapted for the process sector for application at a large integrated steel mill is described, and a simulation model is developed to contrast the “before” and “after” scenarios in detail.
Book

Verification and Validation in Scientific Computing

TL;DR: A comprehensive and systematic development of the basic concepts, principles, and procedures for verification and validation of models and simulations that are described by partial differential and integral equations and the simulations that result from their numerical solution.
Proceedings ArticleDOI

Analysis, modeling and generation of self-similar VBR video traffic

TL;DR: The main findings are that the tail behavior of the marginal bandwidth distribution can be accurately described using “heavy-tailed” distributions and the autocorrelation of the VBR video sequence decays hyperbolically and can be modeled using self-similar processes.
Journal ArticleDOI

Verification and Validation in Computational Fluid Dynamics

TL;DR: An extensive review of the literature in V&V in computational fluid dynamics (CFD) is presented, methods and procedures for assessing V &V are discussed, and a relatively new procedure for estimating experimental uncertainty is given that has proven more effective at estimating random and correlated bias errors in wind-tunnel experiments than traditional methods.