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Economic Analysis of Simulation Selection Problems

Citations

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Cited by:

  1. Powell, Warren B., 2019. "A unified framework for stochastic optimization," European Journal of Operational Research, Elsevier, vol. 275(3), pages 795-821.
  2. Jing Xie & Peter I. Frazier, 2013. "Sequential Bayes-Optimal Policies for Multiple Comparisons with a Known Standard," Operations Research, INFORMS, vol. 61(5), pages 1174-1189, October.
  3. Martin Forster & Paolo Pertile, 2013. "Optimal decision rules for HTA under uncertainty: a wider, dynamic perspective," Health Economics, John Wiley & Sons, Ltd., vol. 22(12), pages 1507-1514, December.
  4. Nikhil Bhat & Vivek F. Farias & Ciamac C. Moallemi & Deeksha Sinha, 2020. "Near-Optimal A-B Testing," Management Science, INFORMS, vol. 66(10), pages 4477-4495, October.
  5. Eric M. Schwartz & Eric T. Bradlow & Peter S. Fader, 2017. "Customer Acquisition via Display Advertising Using Multi-Armed Bandit Experiments," Marketing Science, INFORMS, vol. 36(4), pages 500-522, July.
  6. Stephen E. Chick & Jürgen Branke & Christian Schmidt, 2010. "Sequential Sampling to Myopically Maximize the Expected Value of Information," INFORMS Journal on Computing, INFORMS, vol. 22(1), pages 71-80, February.
  7. Chao Qin & Daniel Russo, 2024. "Optimizing Adaptive Experiments: A Unified Approach to Regret Minimization and Best-Arm Identification," Papers 2402.10592, arXiv.org, revised Jul 2024.
  8. Jun Luo & L. Jeff Hong & Barry L. Nelson & Yang Wu, 2015. "Fully Sequential Procedures for Large-Scale Ranking-and-Selection Problems in Parallel Computing Environments," Operations Research, INFORMS, vol. 63(5), pages 1177-1194, October.
  9. Stephen Chick & Martin Forster & Paolo Pertile, 2017. "A Bayesian decision theoretic model of sequential experimentation with delayed response," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(5), pages 1439-1462, November.
  10. Manel Baucells & Saša Zorc, 2025. "Search in the Dark: The Case with Recall and Gaussian Learning," Operations Research, INFORMS, vol. 73(5), pages 2572-2590, September.
  11. Ilya O. Ryzhov & Warren B. Powell & Peter I. Frazier, 2012. "The Knowledge Gradient Algorithm for a General Class of Online Learning Problems," Operations Research, INFORMS, vol. 60(1), pages 180-195, February.
  12. Bolong Cheng & Arta Jamshidi & Warren Powell, 2015. "Optimal learning with a local parametric belief model," Journal of Global Optimization, Springer, vol. 63(2), pages 401-425, October.
  13. Xuefei Lu & Alessandro Rudi & Emanuele Borgonovo & Lorenzo Rosasco, 2020. "Faster Kriging: Facing High-Dimensional Simulators," Operations Research, INFORMS, vol. 68(1), pages 233-249, January.
  14. Stephen E. Chick & Peter Frazier, 2012. "Sequential Sampling with Economics of Selection Procedures," Management Science, INFORMS, vol. 58(3), pages 550-569, March.
  15. Emre Barut & Warren Powell, 2014. "Optimal learning for sequential sampling with non-parametric beliefs," Journal of Global Optimization, Springer, vol. 58(3), pages 517-543, March.
  16. Woonghee Tim Huh & Michael Jong Kim & Meichun Lin, 2026. "Uncertain Search with Knowledge Transfer," Management Science, INFORMS, vol. 72(2), pages 874-892, February.
  17. Kleijnen, Jack P.C. & Ridder, A.A.N. & Rubinstein, R.Y., 2010. "Variance Reduction Techniques in Monte Carlo Methods," Other publications TiSEM 87680d1a-53c1-4107-ada4-7, Tilburg University, School of Economics and Management.
  18. Raluca M. Ursu & Qingliang Wang & Pradeep K. Chintagunta, 2020. "Search Duration," Marketing Science, INFORMS, vol. 39(5), pages 849-871, September.
  19. Xu Kuang & Stefan Wager, 2024. "Weak Signal Asymptotics for Sequentially Randomized Experiments," Management Science, INFORMS, vol. 70(10), pages 7024-7041, October.
  20. Ilya O. Ryzhov & Warren B. Powell, 2011. "Information Collection on a Graph," Operations Research, INFORMS, vol. 59(1), pages 188-201, February.
  21. Warren B. Powell, 2016. "Perspectives of approximate dynamic programming," Annals of Operations Research, Springer, vol. 241(1), pages 319-356, June.
  22. Victor F. Araman & René A. Caldentey, 2022. "Diffusion Approximations for a Class of Sequential Experimentation Problems," Management Science, INFORMS, vol. 68(8), pages 5958-5979, August.
  23. Peter Jacko, 2016. "Resource capacity allocation to stochastic dynamic competitors: knapsack problem for perishable items and index-knapsack heuristic," Annals of Operations Research, Springer, vol. 241(1), pages 83-107, June.
  24. Francisco Alvarez, 2018. "Decomposing risk in an exploitation–exploration problem with endogenous termination time," Annals of Operations Research, Springer, vol. 261(1), pages 45-77, February.
  25. Daniel Russo, 2020. "Simple Bayesian Algorithms for Best-Arm Identification," Operations Research, INFORMS, vol. 68(6), pages 1625-1647, November.
  26. Daniel Russo, 2021. "Technical Note—A Note on the Equivalence of Upper Confidence Bounds and Gittins Indices for Patient Agents," Operations Research, INFORMS, vol. 69(1), pages 273-278, January.
  27. Jason R. W. Merrick, 2009. "Bayesian Simulation and Decision Analysis: An Expository Survey," Decision Analysis, INFORMS, vol. 6(4), pages 222-238, December.
  28. Yijie Peng & Chun-Hung Chen & Michael C. Fu & Jian-Qiang Hu, 2016. "Dynamic Sampling Allocation and Design Selection," INFORMS Journal on Computing, INFORMS, vol. 28(2), pages 195-208, May.
  29. Haihui Shen & L. Jeff Hong & Xiaowei Zhang, 2021. "Ranking and Selection with Covariates for Personalized Decision Making," INFORMS Journal on Computing, INFORMS, vol. 33(4), pages 1500-1519, October.
  30. Peter I. Frazier & Warren B. Powell, 2010. "Paradoxes in Learning and the Marginal Value of Information," Decision Analysis, INFORMS, vol. 7(4), pages 378-403, December.
  31. Boris Defourny & Ilya O. Ryzhov & Warren B. Powell, 2015. "Optimal Information Blending with Measurements in the L 2 Sphere," Mathematics of Operations Research, INFORMS, vol. 40(4), pages 1060-1088, October.
  32. Ying Zhong & L. Jeff Hong, 2022. "Knockout-Tournament Procedures for Large-Scale Ranking and Selection in Parallel Computing Environments," Operations Research, INFORMS, vol. 70(1), pages 432-453, January.
  33. Stephen E. Chick & Noah Gans & Özge Yapar, 2022. "Bayesian Sequential Learning for Clinical Trials of Multiple Correlated Medical Interventions," Management Science, INFORMS, vol. 68(7), pages 4919-4938, July.
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