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Methodology for determining the acceptability of system designs in uncertain environments
15 references·2 citing·31 second hop
Methodology for determining the acceptability of system designs in uncertain environments (2010)Methodology for determining the acceptabi…Theory of Modeling and Simulation (2018)Theory of Modeling and Simula…Design and Analysis of Simulation Experiments (2015)Design and Analysis of Simula…Robust optimization in simulation: Taguchi and Response Surface Methodology (2009)Robust optimization in simula…Conditional Monte Carlo Estimation of Quantile Sensitivities (2009)Conditional Monte Carlo Estim…A quantile-based approach to system selection (2009)A quantile-based approach to …Uncertainty Settings and Natures of Uncertainty (2008)Uncertainty Settings and Natu…Uncertainty in Industrial Practice (2008)Uncertainty in Industrial Pra…Design and Analysis of Simulation Experiments (2007)Design and Analysis of Simula…A Framework for Validation of Computer Models (2007)A Framework for Validation of…A simulation-based optimization approach to size manufacturing systems (2005)A simulation-based optimizati…Validation of regression metamodels in simulation: Bootstrap approach (2004)Validation of regression meta…Simulation with Arena (1998)Simulation with ArenaThe Concept of Probability in Safety Assessments of Technological Systems (1990)The Concept of Probability in…Statistical tools for simulation practitioners (1990)Statistical tools for simulat…Statistical tools for simulation practitioners (1988)Statistical tools for simulat…Design and Analysis of Simulation Experiments (2018)Design and Analysis of Simula…Regression and Kriging metamodels with their experimental designs in simulation: A review (2016)Regression and Kriging metamo…Simulation Modeling and Analysis. (1983)Response Surface Methodology: Process and Product Optimization Using Designed Experiments (1996)Kriging Metamodeling in Simulation: A Review (2007)Robust Optimization (2009)Sensitivity analysis: A review of recent advances (2015)Design and Analysis of Computer Experiments (1989)Verification, Validation, and Confirmation of Numerical Models in the Earth Sciences (1994)A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code (2000)Calibration, validation, and sensitivity analysis: What's what (2006)Measures of agreement between computation and experiment: Validation metrics (2006)Judgment under Uncertainty: Heuristics and Biases (1974)Judgment under Uncertainty: Heuristics and Biases (1975)On The Quantitative Definition of Risk (1981)Uncertainty and sensitivity analysis in the presence of stochastic and subjective uncertainty (1997)The future of risk assessment (2018)On the Experimental Attainment of Optimum Conditions (1951)Global Sensitivity Analysis. The Primer (2007)A unified framework for stochastic optimization (2018)Discrete simulation-based optimization methods for industrial engineering problems: A systematic literature review (2019)Simulation modeling for analysis (2010)Simulation for manufacturing system design and operation: Literature review and analysis (2014)Simulation: The Practice of Model Development and Use (2014)Verification and validation of simulation models (1995)Testing ecological models: the meaning of validation (1996)Cellular Worlds: A Framework for Modeling Micro—Macro Dynamics (1985)State-of-the-Art Review: A User’s Guide to the Brave New World of Designing Simulation Experiments (2005)Introduction to Sensitivity Analysis (2007)Moment Independent Importance Measures: New Results and Analytical Test Cases (2010)Numerical studies of space-filling designs: optimization of Latin Hypercube Samples and subprojection properties (2013)Verification and validation of simulation models (2012)Simulation optimization: a review of algorithms and applications (2015)
this work references cited by second hop

References

  • 2018Theory of Modeling and Simulation2,961 cited
  • 1998Simulation with Arena1,553 cited
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  • 1990The Concept of Probability in Safety Assessments of Technological Systems629 cited
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  • 2015Design and Analysis of Simulation Experiments371 cited
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  • 2008Uncertainty in Industrial Practice243 cited
  • 2009Robust optimization in simulation: Taguchi and Response Surface Methodology117 cited
  • 2009Conditional Monte Carlo Estimation of Quantile Sensitivities96 cited
  • 2004Validation of regression metamodels in simulation: Bootstrap approach71 cited
  • 1988Statistical tools for simulation practitioners63 cited
  • 2009A quantile-based approach to system selection41 cited
  • 2005A simulation-based optimization approach to size manufacturing systems29 cited
  • 2008Uncertainty Settings and Natures of Uncertainty10 cited

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  • 2018Design and Analysis of Simulation Experiments

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480 cited
  • 2016Regression and Kriging metamodels with their experimental designs in simulation: A review341 cited