Estimation of multiresponse simulation metamodels using control variates
Management Science
Metamodels for simulation input-output relations
WSC '92 Proceedings of the 24th conference on Winter simulation
Proceedings of the 30th conference on Winter simulation
Issues in development of simultaneous forward-inverse metamodels
WSC '05 Proceedings of the 37th conference on Winter simulation
WSC '05 Proceedings of the 37th conference on Winter simulation
Design and Analysis of Experiments
Design and Analysis of Experiments
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In customer-driven design of systems or products, one has performance targets in mind and would like to identify system design parameters that yield the target performance vector. Since most simulation models predict performance given design parameter values, this identification must be done iteratively through an optimization search procedure. In some cases it would be preferable to find design parameter values directly via an explicit inverse model. Regression and other forms of approximation 'metamodels' provide estimates of simulation model outputs as a function of design parameters. It is possible to design fitting experiments (DOE's) that allow simultaneous fitting of both forward and inverse metamodels. This paper discusses the potential for this strategy and shows a simple two-phase DOE strategy using a maxi-min measure of DOE quality.