Input–Output Uncertainty Comparisons for Discrete Optimization via Simulation
Published Online:29 Mar 2019https://doi.org/10.1287/opre.2018.1796
References
- (1985) Advanced Econometrics (Harvard University Press, Cambridge, MA).Google Scholar
- (2012) Tutorial: Input uncertainty in output analysis. Proc. 2012 Winter Simulation Conf. (IEEE Press, Piscataway, NJ), 1–12.Crossref, Google Scholar
- (2013) Robust solutions of optimization problems affected by uncertain probabilities. Management Sci. 59(2):341–357.Link, Google Scholar
- (1992) Optimal designs for multiple comparisons with the best. J. Statist. Planning Inference 30(1):45–62.Crossref, Google Scholar
- (1997) Sensitivity of computer simulation experiments to errors in input data. J. Statist. Comput. Simulation 57(1-4):219–241.Crossref, Google Scholar
- (1998) Two-point methods for assessing variability in simulation output. J. Statist. Comput. Simulation 60(3):183–205.Crossref, Google Scholar
- (2013) A subset selection procedure under input parameter uncertainty. Proc. 2013 Winter Simulation Conf. (IEEE Press, Piscataway, NJ), 463–473.Crossref, Google Scholar
- (2015) Subset selection for simulations accounting for input uncertainty. Proc. 2015 Winter Simulation Conf. (IEEE Press, Piscataway, NJ), 437–446.Crossref, Google Scholar
- (2010) Distributionally robust optimization under moment uncertainty with application to data-driven problems. Oper. Res. 58(3):595–612.Link, Google Scholar
- (2013) Robust selection of the best. Proc. 2013 Winter Simulation Conf. (IEEE Press, Piscataway, NJ), 868–876.Crossref, Google Scholar
- (2015) Handbook of Simulation Optimization. International Series in Operations Research & Management Science (Springer, New York).Crossref, Google Scholar
- (2017) Robust ranking and selection with optimal computing budget allocation. Automatica 81:30–36.Crossref, Google Scholar
- (1996) Multiple Comparisons: Theory and Methods (Chapman & Hall, Boca Raton, FL).Crossref, Google Scholar
- (1985) A procedure for selecting a subset of size m containing the l best of k independent normal populations, with applications to simulation. Comm. Statist. Simulation Comput. B14(3):719–734.Crossref, Google Scholar
- (2016) Input uncertainty and robust analysis in stochastic simulation. Proc. 2016 Winter Simulation Conf. (IEEE Press, Piscataway, NJ), 178–192.Crossref, Google Scholar
- (2015) Single-experiment input uncertainty. J. Simulation 9(3):249–259.Crossref, Google Scholar
- (1993) Robust multiple comparisons under common random numbers. ACM Trans. Model. Comput. Simulation 3(3):225–243.Crossref, Google Scholar
- (1995) Using common random numbers for indifference-zone selection and multiple comparisons in simulation. Management Sci. 41(12):1935–1945.Link, Google Scholar
- (1958) A min-max solution of an inventory problem. Studies in the Mathematical Theory of Inventory and Production (Stanford University Press, Redwood City, CA), 201–209.Google Scholar
- (2003) Confidence Intervals and Regions (John Wiley & Sons, Hoboken, NJ).Crossref, Google Scholar
- (2015) Input uncertainty and indifference-zone ranking & selection. Proc. 2015 Winter Simulation Conf. (IEEE Press, Piscataway, NJ), 414–424.Crossref, Google Scholar
- (2014) Input uncertainty quantification. Proc. 2014 Winter Simulation Conf. (IEEE Press, Piscataway, NJ), 162–176.Crossref, Google Scholar
- (1992) Multivariate stochastic approximation using a simultaneous perturbation gradient approximation. IEEE Trans. Automatic Control 37(3):332–341.Crossref, Google Scholar
- (2006) Stochastic gradient estimation using a single design point. Proc. 2006 Winter Simulation Conf. (IEEE Press, Piscataway, NJ), 390–397.Crossref, Google Scholar

