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The Optimizer's Curse: Skepticism and Postdecision Surprise in Decision Analysis

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  1. Vilkkumaa, Eeva & Liesiö, Juuso & Salo, Ahti, 2014. "Optimal strategies for selecting project portfolios using uncertain value estimates," European Journal of Operational Research, Elsevier, vol. 233(3), pages 772-783.
  2. Johannes Müller-Trede & Shoham Choshen-Hillel & Meir Barneron & Ilan Yaniv, 2017. "The Wisdom of Crowds in Matters of Taste," Discussion Paper Series dp709, The Federmann Center for the Study of Rationality, the Hebrew University, Jerusalem.
  3. Kim, Seokwoo & Choi, Dong Gu, 2024. "A sample robust optimal bidding model for a virtual power plant," European Journal of Operational Research, Elsevier, vol. 316(3), pages 1101-1113.
  4. Becker, Kai Helge, 2016. "An outlook on behavioural OR – Three tasks, three pitfalls, one definition," European Journal of Operational Research, Elsevier, vol. 249(3), pages 806-815.
  5. Jordan Tong & Daniel Feiler, 2017. "A Behavioral Model of Forecasting: Naive Statistics on Mental Samples," Management Science, INFORMS, vol. 63(11), pages 3609-3627, November.
  6. Barbry, Adrien & Anjos, Miguel F. & Delage, Erick & Schell, Kristen R., 2019. "Robust self-scheduling of a price-maker energy storage facility in the New York electricity market," Energy Economics, Elsevier, vol. 78(C), pages 629-646.
  7. Ahmed Saif & Samir Elhedhli, 2019. "Sterilization network design," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 8(1), pages 91-115, March.
  8. Gary J. Summers, 2021. "Friction and Decision Rules in Portfolio Decision Analysis," Decision Analysis, INFORMS, vol. 18(2), pages 101-120, June.
  9. Onesun Steve Yoo & Kevin McCardle, 2020. "The Valuator’s Curse: Decision Analysis of Overvaluation and Disappointment in Acquisition," Decision Analysis, INFORMS, vol. 17(4), pages 299-313, December.
  10. Fleten, Stein-Erik & Bråthen, Espen & Nissen-Meyer, Sigurd-Erik, 2010. "Evaluation of static hedging strategies for hydropower producers in the Nordic market," MPRA Paper 27133, University Library of Munich, Germany.
  11. Wei Liu & Li Yang & Bo Yu, 2022. "Kernel density estimation based distributionally robust mean-CVaR portfolio optimization," Journal of Global Optimization, Springer, vol. 84(4), pages 1053-1077, December.
  12. Vilkkumaa, Eeva & Liesiö, Juuso, 2022. "What causes post-decision disappointment? Estimating the contributions of systematic and selection biases," European Journal of Operational Research, Elsevier, vol. 296(2), pages 587-600.
  13. Yue Zhao & Zhi Chen & Zhenzhen Zhang, 2023. "Distributionally Robust Chance-Constrained p -Hub Center Problem," INFORMS Journal on Computing, INFORMS, vol. 35(6), pages 1361-1382, November.
  14. Maoqi Liu & Li Zheng & Changchun Liu & Zhi‐Hai Zhang, 2023. "From share of choice to buyers' welfare maximization: Bridging the gap through distributionally robust optimization," Production and Operations Management, Production and Operations Management Society, vol. 32(4), pages 1205-1222, April.
  15. Bart P. G. Van Parys & Peyman Mohajerin Esfahani & Daniel Kuhn, 2021. "From Data to Decisions: Distributionally Robust Optimization Is Optimal," Management Science, INFORMS, vol. 67(6), pages 3387-3402, June.
  16. Pourmohammadi, Pardis & Saif, Ahmed, 2023. "Robust metamodel-based simulation-optimization approaches for designing hybrid renewable energy systems," Applied Energy, Elsevier, vol. 341(C).
  17. Keliang Wang & Leonardo Lozano & Carlos Cardonha & David Bergman, 2023. "Optimizing over an Ensemble of Trained Neural Networks," INFORMS Journal on Computing, INFORMS, vol. 35(3), pages 652-674, May.
  18. Maximilian Blesch & Philipp Eisenhauer, 2021. "Robust decision-making under risk and ambiguity," Papers 2104.12573, arXiv.org, revised Oct 2021.
  19. Guopeng Song & Roel Leus, 2022. "Parallel Machine Scheduling Under Uncertainty: Models and Exact Algorithms," INFORMS Journal on Computing, INFORMS, vol. 34(6), pages 3059-3079, November.
  20. Chen, Qingxin & Ma, Shoufeng & Li, Hongming & Zhu, Ning & He, Qiao-Chu, 2024. "Optimizing bike rebalancing strategies in free-floating bike-sharing systems: An enhanced distributionally robust approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 184(C).
  21. Erick Delage & Ahmed Saif, 2022. "The Value of Randomized Solutions in Mixed-Integer Distributionally Robust Optimization Problems," INFORMS Journal on Computing, INFORMS, vol. 34(1), pages 333-353, January.
  22. Georgia Perakis & Melvyn Sim & Qinshen Tang & Peng Xiong, 2023. "Robust Pricing and Production with Information Partitioning and Adaptation," Management Science, INFORMS, vol. 69(3), pages 1398-1419, March.
  23. Jeffrey M. Keisler & Patrick S. Noonan, 2012. "Communicating Analytic Results: A Tutorial for Decision Consultants," Decision Analysis, INFORMS, vol. 9(3), pages 274-292, September.
  24. Alexandre Belloni & Mitchell J. Lovett & William Boulding & Richard Staelin, 2012. "Optimal Admission and Scholarship Decisions: Choosing Customized Marketing Offers to Attract a Desirable Mix of Customers," Marketing Science, INFORMS, vol. 31(4), pages 621-636, July.
  25. Dmitry B. Rokhlin, 2020. "Relative utility bounds for empirically optimal portfolios," Papers 2006.05204, arXiv.org.
  26. Shunichi Ohmori, 2021. "A Predictive Prescription Using Minimum Volume k -Nearest Neighbor Enclosing Ellipsoid and Robust Optimization," Mathematics, MDPI, vol. 9(2), pages 1-16, January.
  27. Qinxiao Yu & Chun Cheng & Ning Zhu, 2022. "Robust Team Orienteering Problem with Decreasing Profits," INFORMS Journal on Computing, INFORMS, vol. 34(6), pages 3215-3233, November.
  28. Daniel Feiler & Jordan Tong, 2022. "From Noise to Bias: Overconfidence in New Product Forecasting," Management Science, INFORMS, vol. 68(6), pages 4685-4702, June.
  29. Ming Zhao & Nickolas Freeman & Kai Pan, 2023. "Robust Sourcing Under Multilevel Supply Risks: Analysis of Random Yield and Capacity," INFORMS Journal on Computing, INFORMS, vol. 35(1), pages 178-195, January.
  30. Aakil M. Caunhye & Douglas Alem, 2023. "Practicable robust stochastic optimization under divergence measures with an application to equitable humanitarian response planning," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 45(3), pages 759-806, September.
  31. Johannes Müller-Trede & Shoham Choshen-Hillel & Meir Barneron & Ilan Yaniv, 2018. "The Wisdom of Crowds in Matters of Taste," Management Science, INFORMS, vol. 64(4), pages 1779-1803, April.
  32. Maximilian Blesch & Philipp Eisenhauer, 2023. "Robust Decision-Making under Risk and Ambiguity," Rationality and Competition Discussion Paper Series 463, CRC TRR 190 Rationality and Competition.
  33. Shehadeh, Karmel S. & Cohn, Amy E.M. & Jiang, Ruiwei, 2020. "A distributionally robust optimization approach for outpatient colonoscopy scheduling," European Journal of Operational Research, Elsevier, vol. 283(2), pages 549-561.
  34. Utsav Sadana & Erick Delage, 2023. "The Value of Randomized Strategies in Distributionally Robust Risk-Averse Network Interdiction Problems," INFORMS Journal on Computing, INFORMS, vol. 35(1), pages 216-232, January.
  35. Ningyuan Chen & Anran Li & Kalyan Talluri, 2021. "Reviews and Self-Selection Bias with Operational Implications," Management Science, INFORMS, vol. 67(12), pages 7472-7492, December.
  36. Robert E. Marks, 2013. "The Satisficer’s Curse," Discussion Papers 2013-28, School of Economics, The University of New South Wales.
  37. Dmitry B. Rokhlin, 2021. "Relative utility bounds for empirically optimal portfolios," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 93(3), pages 437-462, June.
  38. Yiling Zhang & Jin Dong, 2022. "Building Load Control Using Distributionally Robust Chance-Constrained Programs with Right-Hand Side Uncertainty and the Risk-Adjustable Variants," INFORMS Journal on Computing, INFORMS, vol. 34(3), pages 1531-1547, May.
  39. Mellahi, Kamel & Collings, David G., 2010. "The barriers to effective global talent management: The example of corporate élites in MNEs," Journal of World Business, Elsevier, vol. 45(2), pages 143-149, April.
  40. Wang, Duo & Yang, Kai & Yuen, Kum Fai & Yang, Lixing & Dong, Jianjun, 2024. "Hybrid risk-averse location-inventory-allocation with secondary disaster considerations in disaster relief logistics: A distributionally robust approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 186(C).
  41. Salo, Ahti & Doumpos, Michalis & Liesiö, Juuso & Zopounidis, Constantin, 2024. "Fifty years of portfolio optimization," European Journal of Operational Research, Elsevier, vol. 318(1), pages 1-18.
  42. Roozbeh, Iman & Hearne, John & Abbasi, Babak & Ozlen, Melih, 2021. "Decision support for wildfire asset protection: A two-stage stochastic programming approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 155(C).
  43. Ren, Ke & Bidkhori, Hoda & Shen, Zuo-Jun Max, 2024. "Data-driven inventory policy: Learning from sequentially observed non-stationary data," Omega, Elsevier, vol. 123(C).
  44. Saurabh Bansal & Genaro J. Gutierrez, 2020. "Estimating Uncertainties Using Judgmental Forecasts with Expert Heterogeneity," Operations Research, INFORMS, vol. 68(2), pages 363-380, March.
  45. Maximilian Blesch & Philipp Eisenhauer, 2021. "Robust Decision-Making Under Risk and Ambiguity," ECONtribute Discussion Papers Series 104, University of Bonn and University of Cologne, Germany.
  46. Wang, Duo & Yang, Kai & Yang, Lixing & Dong, Jianjun, 2023. "Two-stage distributionally robust optimization for disaster relief logistics under option contract and demand ambiguity," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 170(C).
  47. Cheng, Chun & Yu, Qinxiao & Adulyasak, Yossiri & Rousseau, Louis-Martin, 2024. "Distributionally robust facility location with uncertain facility capacity and customer demand," Omega, Elsevier, vol. 122(C).
  48. John R. Birge, 2023. "Uses of Sub-sample Estimates to Reduce Errors in Stochastic Optimization Models," Papers 2310.07052, arXiv.org.
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