Metamodels for simulation input-output relations
WSC '92 Proceedings of the 24th conference on Winter simulation
Proceedings of the 30th conference on Winter simulation
A framework for Response Surface Methodology for simulation optimization
Proceedings of the 32nd conference on Winter simulation
Efficient Global Optimization of Expensive Black-Box Functions
Journal of Global Optimization
A gradient—regression search procedure for simulation experimentation
WSC '74 Proceedings of the 7th conference on Winter simulation - Volume 2
Simulation-based optimization: practical introduction to simulation optimization
Proceedings of the 35th conference on Winter simulation: driving innovation
Global Optimization of Stochastic Black-Box Systems via Sequential Kriging Meta-Models
Journal of Global Optimization
Automated response surface methodology for stochastic optimization models with unknown variance
WSC '04 Proceedings of the 36th conference on Winter simulation
Simulation optimization: a review, new developments, and applications
WSC '05 Proceedings of the 37th conference on Winter simulation
Neural Networks for Applied Sciences and Engineering
Neural Networks for Applied Sciences and Engineering
Proceedings of the 38th conference on Winter simulation
The impact of ordinal on response surface methodology
Proceedings of the 38th conference on Winter simulation
Regression models and experimental designs: a tutorial for simulation analysts
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
Metamodeling for cycle time-throughput-product mix surfaces using progressive model fitting
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
Kriging metamodeling in constrained simulation optimization: an explorative study
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
Stochastic kriging for simulation metamodeling
Proceedings of the 40th Conference on Winter Simulation
Design of experiments: overview
Proceedings of the 40th Conference on Winter Simulation
Discrete stochastic optimization using linear interpolation
Proceedings of the 40th Conference on Winter Simulation
Design and Analysis of Simulation Experiments
Design and Analysis of Simulation Experiments
On direct gradient enhanced simulation metamodels
Proceedings of the Winter Simulation Conference
Proceedings of the Winter Simulation Conference
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Many iterative optimization methods are designed to be used in conjunction with deterministic objective functions. These optimization methods can be difficult to apply to an objective generated by a discrete-event simulation, due to the stochastic nature of the response(s) and the potentially extensive run times. A metamodel aids simulation optimization by providing a deterministic objective with run times that are generally much shorter than the original discrete-event simulation. Polynomial metamodels generally provide only local approximations, and so a series of metamodels must be fit as the optimization progresses. Other classes of metamodels can provide global fit; fitting can be done either by constructing the global model once at the start of the optimization, or by using the optimization results to identify additional discrete-event runs to refine the global model. This tutorial surveys both local and global metamodel-based optimization methods.