An experimental procedure for simulation response surface model identification
Communications of the ACM
Validation of correlation-induction strategies for simulation experiments
WSC '85 Proceedings of the 17th conference on Winter simulation
Sensitivity analysis via likelihood ratios
WSC '86 Proceedings of the 18th conference on Winter simulation
Using control variates to estimate multiresponse simulation metamodels
WSC '86 Proceedings of the 18th conference on Winter simulation
Stochastic approximation for Monte Carlo optimization
WSC '86 Proceedings of the 18th conference on Winter simulation
Simulation optimization using frequency domain methods
WSC '86 Proceedings of the 18th conference on Winter simulation
Estimation procedures based on control variates with known covariance matrix
WSC '87 Proceedings of the 19th conference on Winter simulation
Metamodel estimation using integrated correlation methods
WSC '87 Proceedings of the 19th conference on Winter simulation
A tutorial on simulation optimization
WSC '92 Proceedings of the 24th conference on Winter simulation
Multicriteria optimization of simulation models
WSC '91 Proceedings of the 23rd conference on Winter simulation
Simulation optimization methodologies
Proceedings of the 31st conference on Winter simulation: Simulation---a bridge to the future - Volume 1
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As a tool for gradient estimation and sensitivity analysis in discrete simulation, response surface methodology possesses noteworthy advantages in comparison to some of the more recently developed techniques. This paper surveys future directions for research, development, and application of response surface methodology in discrete simulation.