Statistical tools for simulation practitioners
Statistical tools for simulation practitioners
Sensitivity analysis of model output: an investigation of new techniques
Computational Statistics & Data Analysis
Sensitivity analysis of model output: performance of the iterated fractional factorial design method
Computational Statistics & Data Analysis
Sensitivity analysis and optimization in simulation: design of experiments and case studies
WSC '95 Proceedings of the 27th conference on Winter simulation
Proceedings of the 31st conference on Winter simulation: Simulation---a bridge to the future - Volume 1
Neural Networks for Statistical Modeling
Neural Networks for Statistical Modeling
Response Surface Methodology: Process and Product in Optimization Using Designed Experiments
Response Surface Methodology: Process and Product in Optimization Using Designed Experiments
Applications of Neural Networks in Electromagnetics
Applications of Neural Networks in Electromagnetics
Proceedings of the 35th conference on Winter simulation: driving innovation
Designing simulation experiments
WSC '04 Proceedings of the 36th conference on Winter simulation
Controlled sequential factorial design for simulation factor screening
WSC '05 Proceedings of the 37th conference on Winter simulation
A hybrid method for simulation factor screening
Proceedings of the 38th conference on Winter simulation
Important factors in screening for colorectal cancer
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
Improving risk assessment methodology: a statistical design of experiments approach
Proceedings of the 2nd international conference on Security of information and networks
Combining strong and screening designs for large-scale simulation optimization
Proceedings of the Winter Simulation Conference
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Once a simulation model is developed, designed experiments may be employed to efficiently optimize the system. Designed experiments are used on "real" production systems as well. The first step is to screen for important independent variables. Several screening methods are compared and contrasted in terms of efficiency, effectiveness, and robustness. These screening methods range from the classical factorial designs and two-stage group screening to new, more novel designs including sequential bifurcation (SB) and iterated fractional factorial designs (IFFD). Conditions for the use of the methods are provided along with references on how to use them.