Conformal Inverse Optimization for Adherence-Aware Prescriptive Analytics

Published Online:https://doi.org/10.1287/opre.2024.1376

References

  • Ahuja RK, Orlin JB (2001) Inverse optimization. Oper. Res. 49(5):771–783.Link, Google Scholar
  • Arun I, Venkatapathi M (2025) An O(n) algorithm for generating uniform random vectors in n-dimensional cones. Sankhya A 87:327–348.Crossref, Google Scholar
  • Aswani A, Shen ZJM, Siddiq A (2018) Inverse optimization with noisy data. Oper. Res. 66(3):870–892.Link, Google Scholar
  • Aswani A, Shen ZJM, Siddiq A (2019) Data-driven incentive design in the Medicare shared savings program. Oper. Res. 67(4):1002–1026.Abstract, Google Scholar
  • Babier A, Mahmood R, McNiven AL, Diamant A, Chan TC (2020) Knowledge-based automated planning with three-dimensional generative adversarial networks. Medical Phys. 47(2):297–306.Crossref, Google Scholar
  • Bärmann A, Martin A, Pokutta S, Schneider O (2018) An online-learning approach to inverse optimization. Preprint, submitted October 30, https://arxiv.org/abs/1810.12997.Google Scholar
  • Bastani H, Bastani O, Sinchaisri WP (2025) Improving human sequential decision making with reinforcement learning. Management Sci. 72(1):733–755.Link, Google Scholar
  • Ben-Tal A, Nemirovski A (1999) Robust solutions of uncertain linear programs. Oper. Res. Lett. 25(1):1–13.Crossref, Google Scholar
  • Ben-Tal A, Nemirovski A (2000) Robust solutions of linear programming problems contaminated with uncertain data. Math. Programming 88:411–424.Crossref, Google Scholar
  • Berthet Q, Blondel M, Teboul O, Cuturi M, Vert JP, Bach F (2020) Learning with differentiable perturbed optimizers. Adv. Neural Inform. Processing Systems, vol. 33 (Curran Associates Inc., Red Hook, NY), 9508–9519.Google Scholar
  • Bertsimas D, Sim M (2004) The price of robustness. Oper. Res. 52(1):35–53.Link, Google Scholar
  • Bertsimas D, Gupta V, Kallus N (2018) Data-driven robust optimization. Math. Programming 167:235–292.Crossref, Google Scholar
  • Bertsimas D, Gupta V, Paschalidis IC (2015) Data-driven estimation in equilibrium using inverse optimization. Math. Programming 153:595–633.Crossref, Google Scholar
  • Bertsimas D, Pachamanova D, Sim M (2004) Robust linear optimization under general norms. Oper. Res. Lett. 32(6):510–516.Crossref, Google Scholar
  • Besbes O, Fonseca Y, Lobel I (2025) Contextual inverse optimization: Offline and online learning. Oper. Res. 73(1):424–443.Link, Google Scholar
  • Birge JR, Li X, Sun C (2022a) Stochastic inverse optimization. Accessed January 20, 2024, https://perma.cc/8T8L-MZZE.Google Scholar
  • Birge JR, Chan TCY, Pavlin JM, Zhu IY (2022b) Spatial price integration in commodity markets with capacitated transportation networks. Oper. Res. 70(3):1739–1761.Link, Google Scholar
  • Burton D, Toint PL (1992) On an instance of the inverse shortest paths problem. Math. Programming 53(1):45–61.Crossref, Google Scholar
  • Burton JW, Stein MK, Jensen TB (2020) A systematic review of algorithm aversion in augmented decision making. J. Behav. Decision Making 33(2):220–239.Crossref, Google Scholar
  • Chan TCY, Kaw N (2020) Inverse optimization for the recovery of constraint parameters. Eur. J. Oper. Res. 282(2):415–427.Crossref, Google Scholar
  • Chan TCY, Lee T, Terekhov D (2019) Inverse optimization: Closed-form solutions, geometry, and goodness of fit. Management Sci. 65(3):1115–1135.Link, Google Scholar
  • Chan TCY, Mahmood R, Zhu IY (2023a) Inverse optimization: Theory and applications. Oper. Res. 73(2):1046–1074.Link, Google Scholar
  • Chan TCY, Craig T, Lee T, Sharpe MB (2014) Generalized inverse multiobjective optimization with application to cancer therapy. Oper. Res. 62(3):680–695.Link, Google Scholar
  • Chan TCY, Mahmood R, O’Connor DL, Stone D, Unger S, Wong RK, Zhu IY (2023b) Got (optimal) milk? Pooling donations in human milk banks with machine learning and optimization. Manufacturing Service Oper. Management 27(6):1721–1739.Link, Google Scholar
  • Chen Z, Zhao L (2025) Combining forecasts from multiple experts for multiple variables. Management Sci. 72(8):6542–6558.Link, Google Scholar
  • Chen V, Liao QV, Wortman Vaughan J, Bansal G (2023) Understanding the role of human intuition on reliance in human-AI decision-making with explanations. Proc. ACM Human-Comput. Interaction, vol. 7, 1–32.Google Scholar
  • Chen L, Ramachandra A, Rujeerapaiboon N (2025) Robust data-driven CARA optimization. Preprint, submitted February 24, https://doi.org/10.2139/ssrn.5130565.Google Scholar
  • Chenreddy AR, Bandi N, Delage E (2022) Data-driven conditional robust optimization. Adv. Neural Inform. Processing Systems, vol. 35, 9525–9537.Google Scholar
  • Ciocan DF, Mišić VV (2022) Interpretable optimal stopping. Management Sci. 68(3):1616–1638.Link, Google Scholar
  • City of Toronto (2020) City of Toronto open data. Accessed September 15, 2020, https://open.toronto.ca/.Google Scholar
  • Delage E, Ye Y (2010) Distributionally robust optimization under moment uncertainty with application to data-driven problems. Oper. Res. 58(3):595–612.Link, Google Scholar
  • Dietvorst BJ, Simmons JP, Massey C (2018) Overcoming algorithm aversion: People will use imperfect algorithms if they can (even slightly) modify them. Management Sci. 64(3):1155–1170.Link, Google Scholar
  • Dong C, Zeng B (2021) Wasserstein distributionally robust inverse multiobjective optimization. Proc. AAAI Conf. Artificial Intelligence, vol. 35, 5914–5921.Google Scholar
  • Dong C, Chen Y, Zeng B (2018) Generalized inverse optimization through online learning. Adv. Neural Inform. Processing Systems, vol. 31.Google Scholar
  • DoorDash (2024) Bike delivery strategies. Accessed June 12, 2024, https://perma.cc/M98U-A8LC.Google Scholar
  • Elmachtoub AN, Grigas P (2022) Smart “predict, then optimize.” Management Sci. 68(1):9–26.Link, Google Scholar
  • Fu G, Zhang P, Lei D, Qi W, Shen ZJM (2023) Learning for guiding: A pairwise inverse reinforcement learning framework for last-mile deliveries. Preprint, submitted November 30, https://doi.org/10.2139/ssrn.4639706.Google Scholar
  • Gao R, Kleywegt A (2023) Distributionally robust stochastic optimization with Wasserstein distance. Math. Oper. Res. 48(2):603–655.Link, Google Scholar
  • Global Times (2021) Panicked woman rider jumps out of car, breaking bones; car-hailing platform probed. Accessed August 1, 2024, https://www.globaltimes.cn/page/202106/1226697.shtml.Google Scholar
  • Goerigk M, Kurtz J (2023) Data-driven robust optimization using deep neural networks. Comput. Oper. Res. 151:106087.Crossref, Google Scholar
  • Grand-Clément J, Pauphilet J (2024) The best decisions are not the best advice: Making adherence-aware recommendations. Management Sci. 72(1):667–692.Link, Google Scholar
  • Harsanyi JC (1955) Cardinal welfare, individualistic ethics, and interpersonal comparisons of utility. J. Political Econom. 63(4):309–321.Crossref, Google Scholar
  • Hong LJ, Huang Z, Lam H (2021) Learning-based robust optimization: Procedures and statistical guarantees. Management Sci. 67(6):3447–3467.Link, Google Scholar
  • Hu X, Cirit O, Binaykiya T, Hora R (2022) DeepETA: How Uber predicts arrival times using deep learning. Uber engineering blog. Accessed January 19, 2024, https://perma.cc/VBR7-E37Z.Google Scholar
  • Kawaguchi K (2021) When will workers follow an algorithm? A field experiment with a retail business. Management Sci. 67(3):1670–1695.Link, Google Scholar
  • Kesavan S, Kushwaha T (2020) Field experiment on the profit implications of merchants’ discretionary power to override data-driven decision-making tools. Management Sci. 66(11):5182–5190.Link, Google Scholar
  • Kizilcec RF (2016) How much information? Effects of transparency on trust in an algorithmic interface. Proc. 2016 CHI Conf. Human Factors Comput. Systems, 2390–2395.Google Scholar
  • Kocuk B (2021) Rational polyhedral outer-approximations of the second-order cone. Discrete Optim. 40:100643.Crossref, Google Scholar
  • Lin B, Chan TC, Saxe S (2021) The impact of COVID-19 cycling infrastructure on low-stress cycling accessibility: A case study in the City of Toronto. Findings.Crossref, Google Scholar
  • Liu S, Jiang H (2022) Personalized route recommendation for ride-hailing with deep inverse reinforcement learning and real-time traffic conditions. Transportation Res. Part E Logist. Transportation Rev. 164:102780.Crossref, Google Scholar
  • Liu S, He L, Shen ZJM (2021) On-time last-mile delivery: Order assignment with travel-time predictors. Management Sci. 67(7):4095–4119.Link, Google Scholar
  • Liu S, Siddiq A, Zhang J (2024) Planning bike lanes with data: Ridership, congestion, and path selection. Management Sci. 71(9):7631–7654.Link, Google Scholar
  • Liu M, Tang X, Xia S, Zhang S, Zhu Y, Meng Q (2023) Algorithm aversion: Evidence from ridesharing drivers. Management Sci. 72(1):193–203.Link, Google Scholar
  • Lobo MS, Yao D (2025) Fat tails in human judgment: Empirical evidence and implications for the aggregation of estimates and forecasts. Management Sci. 72(3):2364–2379.Link, Google Scholar
  • Mandi J, Bucarey V, Tchomba MMK,Guns T (2022) Decision-focused learning: Through the lens of learning to rank. Internat. Conf. Machine Learn. (PMLR), 14935–14947.Google Scholar
  • Martínez-de Albéniz V, Krigul C (2025) Human agency in last mile delivery. https://perma.cc/6XM7-7ZJE.Google Scholar
  • Merchán D, Arora J, Pachon J, Konduri K, Winkenbach M, Parks S, Noszek J (2022) 2021 Amazon last mile routing research challenge: Data set. Transportation Sci. 58(1):8–11.Link, Google Scholar
  • Mohajerin Esfahani P, Shafieezadeh-Abadeh S, Hanasusanto GA, Kuhn D (2018) Data-driven inverse optimization with imperfect information. Math. Programming 167:191–234.Crossref, Google Scholar
  • OpenStreetMap (2017) Planet dump. https://planet.osm.org.Google Scholar
  • Rönnqvist M, Svenson G, Flisberg P, Jönsson LE (2017) Calibrated route finder: Improving the safety, environmental consciousness, and cost effectiveness of truck routing in Sweden. Interfaces 47(5):372–395.Link, Google Scholar
  • Sadana U, Chenreddy A, Delage E, Forel A, Frejinger E, Vidal T (2025) A survey of contextual optimization methods for decision-making under uncertainty. Eur. J. Oper. Res. 320(2):271–289.Crossref, Google Scholar
  • Shahmoradi Z, Lee T (2022) Quantile inverse optimization: Improving stability in inverse linear programming. Oper. Res. 70(4):2538–2562.Link, Google Scholar
  • Shang C, Huang X, You F (2017) Data-driven robust optimization based on kernel learning. Comput. Chemical Engrg. 106:464–479.Crossref, Google Scholar
  • Simon HA (1955) A behavioral model of rational choice. Quart. J. Econom. 69(1):99–118.Crossref, Google Scholar
  • Sun C, Liu L, Li X (2023) Predict-then-calibrate: A new perspective of robust contextual LP. Adv. Neural Inform. Processing Systems, vol. 36, 17713–17741.Google Scholar
  • Sun J, Zhang DJ, Hu H, Van Mieghem JA (2022) Predicting human discretion to adjust algorithmic prescription: A large-scale field experiment in warehouse operations. Management Sci. 68(2):846–865.Link, Google Scholar
  • Travel Modelling Group (2016) GTAModel V4 introduction. Accessed November 20, 2020, https://perma.cc/7CUU-BMHB.Google Scholar
  • Turner SD, Chan TCY (2013) Examining the LEED rating system using inverse optimization. J. Solar Energy Engrg. 135(4):040901.Crossref, Google Scholar
  • Vovk V, Gammerman A, Shafer G (2005) Algorithmic Learning in a Random World, vol. 29 (Springer).Google Scholar
  • Wang M, Ban GY, Li X (2026) The human-AI-human newsvendor: Behavioral biases, partial adherence and learning. Preprint, submitted January 22, https://doi.org/10.2139/ssrn.5999076.Google Scholar
  • Wang Y, He L, Qi Z, Minner S (2025) Dispatch or hold? An inverse optimization and reinforcement learning approach for multi-objective on-demand delivery. Preprint, submitted December 1, https://doi.org/10.2139/ssrn.5839702.Google Scholar
  • Wei K, Vaze V (2018) Modeling crew itineraries and delays in the national air transportation system. Transportation Sci. 52(5):1276–1296.Link, Google Scholar
  • Wilder B, Dilkina B, Tambe M (2019) Melding the data-decisions pipeline: Decision-focused learning for combinatorial optimization. Proc. AAAI Conf. Artificial Intelligence, vol. 33, 1658–1665.Google Scholar
  • Yin M, Wortman Vaughan J, Wallach H (2019) Understanding the effect of accuracy on trust in machine learning models. Proc. 2019 CHI Conf. Human Factors Comput. Systems, 1–12.Google Scholar
  • Yousefi N (2023) Inverse optimization and its applications in measuring clinical pathway concordance. Unpublished PhD thesis, University of Toronto, Ontario.Google Scholar
  • Zattoni Scroccaro P, Atasoy B, Mohajerin Esfahani P (2024a) Learning in inverse optimization: Incenter cost, augmented suboptimality loss, and algorithms. Oper. Res. 73(5):2661–2679.Link, Google Scholar
  • Zattoni Scroccaro P, van Beek P, Mohajerin Esfahani P, Atasoy B (2024b) Inverse optimization for routing problems. Transportation Sci. 59(2):301–321.Link, Google Scholar
  • Zimmermann M, Mai T, Frejinger E (2017) Bike route choice modeling using GPS data without choice sets of paths. Transportation Res. Part C Emerging Tech. 75:183–196.Crossref, Google Scholar
INFORMS site uses cookies to store information on your computer. Some are essential to make our site work; Others help us improve the user experience. By using this site, you consent to the placement of these cookies. Please read our Privacy Statement to learn more.