The simulation metamodel
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.
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analysis of simulation analytic antithetic variates applied assignment rule coefficients common random numbers computer simulation computer simulation experiments control variates cross validation David Kelton decision support system design and analysis experimental design experimentwise error rate Fishman fractional factorial design holdout sample Hotelling's T2 test Houck independent replications input factors Jack P.C. Kelton Kleijnen linear regression linear regression model M/M/s Queuing System Madu and Kuei Management Science MANOVA measures of effectiveness metamodel developed metamodel estimation Metamodel Validation multiple response simulation multivariate metamodel multivariate statistical Myers Naylor Operations Research optimization procedure pure error Queuing System Simulation random number streams real system real-world system regression analysis regression metamodel Research Logistics Quarterly response surface methodology response variable sensitivity analysis simulation analysis simulation metamodeling experiment simulation model simulation output simulation runs simulation study statistical analysis steady-state System Simulation Metamodel system under study Taguchi univariate validating the simulation values variance reduction techniques Winter Simulation Conference