Overview

Researchers develop simulation models that emulate real-world situations. While these simulation models are simpler than the real situation, they are still quite complex and time consuming to develop. It is at this point that metamodelling can be used to help build a simulation study based on a complex model. A metamodel is a simpler, analytical model, auxiliary to the simulation model, which is used to better understand the more complex model, to test hypotheses about it and to provide a framework for improving the simulation study. The use of metamodels allows the researcher to work with a set of mathematical functions and analytical techniques to test simulations without the costly running and re-running of complex computer programs. In addition, metamodels have other advantages and, as a result, they are being used in a variety of ways: model simplification, optimization, model interpretation, generalization to other models of similar systems, efficient sensitivity analysis, and the use of the metamodel's mathematical functions to answer questions about different variables within a simulation study. This book explores the use of metamodels to test simulations.

Full Product Details

Author:   Linda Weiser Friedman
Publisher:   Springer
Imprint:   Springer
Edition:   1996 ed.
Dimensions:   Width: 15.50cm , Height: 1.40cm , Length: 23.50cm
Weight:   1.100kg
ISBN:  

9780792396482

ISBN 10:   0792396480
Pages:   202
Publication Date:   30 November 1995
Audience:   Professional and scholarly ,  General/trade ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print  
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Table of Contents

1 Introduction To Simulation Modeling And Metamodeling.- 1 References.- 2 The Simulation Model And Metamodel.- The Simulation Model.- The Simulation Metamodel.- Levels of Abstraction in Simulation.- 2 References.- 3 The Metamodel In Perspective: Statistical Considerations In Simulation Experiments.- Some Statistical Considerations.- Strategic Considerations.- Tactical Considerations.- Experimental Design in Simulation.- The Multiple Response Simulation Experiment.- 3 References.- 4 Metamodeling.- Building the Simulation Metamodel.- Steps in Metamodeling.- Validating the Simulation Metamodel.- Example: A Metamodel for the M/M/s Queuing System.- The Simulation Model.- The Simulation Metamodel.- Validating the Simulation Metamodel.- Using the Simulation Metamodel.- 4 References.- 5 Survey Of Current Research.- Metamodel Usage.- Sensitivity Analysis.- Optimization.- Decision Support.- Applications.- Manufacturing.- Ecology.- Computer Performance Evaluation.- Hospital Planning.- Military.- Metamodel Methodology.- Method of Statistical Analysis.- Sample Size.- Variance Reduction.- The Metamodeling Experiment.- Metamodel Validation.- Metamodeling: Assessing the Technique.- Combining Metamodeling with other Model Types.- 5 References.- 6 Metamodeling: Some Additional Examples.- Example: A Time-shared Computer System.- Example: An Inventory Control System.- 6 References.- Appendix: The Linear Regression Model.

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