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 metamodeling 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 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.
Auflage
Sprache
Verlagsort
Zielgruppe
Für Beruf und Forschung
Research
Illustrationen
Maße
Höhe: 241 mm
Breite: 160 mm
Dicke: 18 mm
Gewicht
ISBN-13
978-0-7923-9648-2 (9780792396482)
DOI
10.1007/978-1-4613-1299-4
Schweitzer Klassifikation
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.
