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Original Articles

Quickly Assessing Contributions to Input Uncertainty

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Stewart Robinson. (2023) Exploring the relationship between simulation model accuracy and complexity. Journal of the Operational Research Society 74:9, pages 1992-2011.
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Canan G. Corlu, Bahar Biller & Sridhar Tayur. (2019) Driving inventory system simulations with limited demand data: Insights from the newsvendor problem. Journal of Simulation 13:2, pages 152-162.
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Alp Akcay & Bahar Biller. (2018) Input uncertainty in stochastic simulations in the presence of dependent discrete input variables . Journal of Simulation 12:4, pages 1-12.
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Alp Akcay & Canan G. Corlu. (2017) Simulation of inventory systems with unknown input models: a data-driven approach. International Journal of Production Research 55:19, pages 5826-5840.
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Paul D. Arendt, Daniel W. Apley & Wei Chen. (2016) A preposterior analysis to predict identifiability in the experimental calibration of computer models. IIE Transactions 48:1, pages 75-88.
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Articles from other publishers (28)

Yi ZhuJing Dong & Henry Lam. (2023) Uncertainty Quantification and Exploration for Reinforcement Learning. Operations Research.
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Henry Lam. (2022) Cheap Bootstrap for Input Uncertainty Quantification. Cheap Bootstrap for Input Uncertainty Quantification.
Motong Chen, Zhenyuan Liu & Henry Lam. (2022) Distributional Input Uncertainty. Distributional Input Uncertainty.
Di Wu, Yuhao Wang & Enlu Zhou. (2022) Data-Driven Ranking and Selection Under Input Uncertainty. Operations Research.
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Juan Ungredda, Michael Pearce & Juergen Branke. (2022) Bayesian Optimisation vs. Input Uncertainty Reduction. ACM Transactions on Modeling and Computer Simulation 32:3, pages 1-26.
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Henry Lam & Huajie Qian. (2022) Subsampling to Enhance Efficiency in Input Uncertainty Quantification. Operations Research 70:3, pages 1891-1913.
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Russell R. Barton, Henry Lam & Eunhye Song. 2022. The Palgrave Handbook of Operations Research. The Palgrave Handbook of Operations Research 573 620 .
Barry L. Nelson & Linda PeiBarry L. Nelson & Linda Pei. 2021. Foundations and Methods of Stochastic Simulation. Foundations and Methods of Stochastic Simulation 179 197 .
Haowei Wang, Szu Hui Ng & Xun Zhang. (2020) A Gaussian Process Based Algorithm for Stochastic Simulation Optimization with Input Distribution Uncertainty. A Gaussian Process Based Algorithm for Stochastic Simulation Optimization with Input Distribution Uncertainty.
Barry L. Nelson, Alan T. K. WanGuohua ZouXinyu Zhang & Xi Jiang. (2020) Reducing Simulation Input-Model Risk via Input Model Averaging. INFORMS Journal on Computing.
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Helin Zhu, Tianyi Liu & Enlu Zhou. (2020) Risk Quantification in Stochastic Simulation under Input Uncertainty. ACM Transactions on Modeling and Computer Simulation 30:1, pages 1-24.
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Canan G. Corlu, Alp Akcay & Wei Xie. (2020) Stochastic simulation under input uncertainty: A Review. Operations Research Perspectives 7, pages 100162.
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L. Jeff Hong & Guangxin Jiang. (2019) Offline Simulation Online Application: A New Framework of Simulation-Based Decision Making. Asia-Pacific Journal of Operational Research 36:06, pages 1940015.
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Ben M. Feng & Eunhye Song. (2019) Efficient Input Uncertainty Quantification Via Green Simulation Using Sample Path Likelihood Ratios. Efficient Input Uncertainty Quantification Via Green Simulation Using Sample Path Likelihood Ratios.
Henry Lam & Huajie Qian. (2019) Random Perturbation and Bagging to Quantify Input Uncertainty. Random Perturbation and Bagging to Quantify Input Uncertainty.
Wei Xie, Bo Wang & Pu Zhang. (2019) Metamodel-Assisted Sensitivity Analysis for Controlling the Impact of Input Uncertainty. Metamodel-Assisted Sensitivity Analysis for Controlling the Impact of Input Uncertainty.
Soumyadip GhoshHenry Lam. (2019) Robust Analysis in Stochastic Simulation: Computation and Performance Guarantees. Operations Research 67:1, pages 232-249.
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Bahar Biller, Stephan R. Biller, Onur Dulgeroglu & Canan G. Corlu. (2017) The role of learning on industrial simulation design and analysis. The role of learning on industrial simulation design and analysis.
Alp Akcay & Tugce Martagan. (2017) Simulation-based production planning for engineer-to-order systems with random yield. Simulation-based production planning for engineer-to-order systems with random yield.
Amirhossein Meisami, Mark P. Van Oyen & Henry Lam. (2017) Uncertainty quantification on simulation analysis driven by random forests. Uncertainty quantification on simulation analysis driven by random forests.
Lucy E. Morgan, Barry L. Nelson, Andrew C. Titman & David J. Worthington. (2017) Detecting bias due to input modelling in computer simulation. Detecting bias due to input modelling in computer simulation.
Russell Cheng. (2017) History of input modeling. History of input modeling.
Enlu Zhou & Di Wu. 2017. Advances in Modeling and Simulation. Advances in Modeling and Simulation 219 247 .
Alp Akcay & Tugce Martagan. (2016) Stochastic simulation under input uncertainty for contract-manufacturer selection in pharmaceutical industry. Stochastic simulation under input uncertainty for contract-manufacturer selection in pharmaceutical industry.
Lucy E. Morgan, Andrew C. Titman, David J. Worthington & Barry L. Nelson. (2016) Input uncertainty quantification for simulation models with piecewise-constant non-stationary Poisson arrival processes. Input uncertainty quantification for simulation models with piecewise-constant non-stationary Poisson arrival processes.
Barry L. Nelson. (2016) Technology transfer of simulation analysis methodology: One man's opinion. Technology transfer of simulation analysis methodology: One man's opinion.
Henry Lam. (2016) Advanced tutorial: Input uncertainty and robust analysis in stochastic simulation. Advanced tutorial: Input uncertainty and robust analysis in stochastic simulation.
Eunhye Song, Barry L. Nelson & Jeremy Staum. (2016) Shapley Effects for Global Sensitivity Analysis: Theory and Computation. SIAM/ASA Journal on Uncertainty Quantification 4:1, pages 1060-1083.
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