Empirical model-building and response surface
Empirical model-building and response surface
Statistical tools for simulation practitioners
Statistical tools for simulation practitioners
Response surfaces: designs and analyses
Response surfaces: designs and analyses
Metamodels for simulation input-output relations
WSC '92 Proceedings of the 24th conference on Winter simulation
Regular Article: Topology and Invertible Maps
Advances in Applied Mathematics
Response Surface Methodology: Process and Product in Optimization Using Designed Experiments
Response Surface Methodology: Process and Product in Optimization Using Designed Experiments
Simulation Modeling and Analysis
Simulation Modeling and Analysis
Design and Analysis of Experiments
Design and Analysis of Experiments
A two-phase maxi-min algorithm for forward-inverse experiment design
Proceedings of the 38th conference on Winter simulation
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Metamodels provide estimates of simulation outputs as a function of design parameters. Often in the design of a system or product, one has performance targets in mind, and would like to identify system design parameters that would yield the target performance vector. Typically this is handled iteratively through an optimization search procedure. As an alternative, one could map system performance requirements to design parameters via an inverse metamodel. Inverse metamodels can be fitted 'for free,' given an experiment design to fit several forward models for multiple performance measures. This paper discusses this strategy, and some of the issues that must be resolved to make the approach practical.