Stochastic Optimization Model with Exogenous and Decision-Dependent Uncertainty for Medical Evacuation

Published Online:https://doi.org/10.1287/ijoc.2024.0986

References

  • Ahmed S, Xie W (2018) Relaxations and approximations of chance constraints under finite distributions. Math. Program. 170(1):43–65.CrossrefGoogle Scholar
  • Apap RM, Grossmann IE (2017) Models and computational strategies for multistage stochastic programming under endogenous and exogenous uncertainties. Comput. Chemical Engrg. 103(1):233–274.CrossrefGoogle Scholar
  • Aringhieri R, Bruni ME, Khodaparasti S, van Essen JT (2018) Emergency medical services and beyond: Addressing new challenges through a wide literature review. Comput. Oper. Res. 78(1):349–368.Google Scholar
  • Bailey J, Spott MA, Costanzo G, Dunne J, Dorlac W, Eastridge B (2012) Joint trauma system: Development, conceptual framework and optimal elements. Fort Sam Houston, U.S. Department of Defense, U.S. Army Institute of Surgical Research, San Antonio, TX.Google Scholar
  • Bastian N, Fulton LV, Mitchell R, Pollard W, Wierschem D, Wilson R (2012) The future of vertical lift: Initial insights for aircraft capability and medical planning. Mil. Med. 177(7):863–869.CrossrefGoogle Scholar
  • Belotti P, Lee J, Liberti L, Margot F, Wächter A (2009) Branching and bounds tightening techniques for non-convex MINLP. Optim. Methods Softw. 24(4–5):597–634.CrossrefGoogle Scholar
  • Biswas S, Turan H, Elsawah S, Richmond M, Cao T (2025) The future of military medical evacuation: Literature analysis focused on the potential adoption of emerging technologies and advanced decision-analysis techniques. J. Defense Modeling Simulat. Appl., Methodol. Tech. 22(3):279–308.CrossrefGoogle Scholar
  • Bonami P, Lee J, Leyffer S, Wächter A (2013) On branching rules for convex mixed-integer nonlinear optimization. ACM J. Exp. Algorithmics 18(2):6:4–6:31.Google Scholar
  • Cho SH, Jang H, Lee T, Turner J (2014) Simultaneous location of trauma centers and helicopters for emergency medical service planning. Oper. Res. 62(4):751–771.LinkGoogle Scholar
  • COIN-OR (2018) Branch–cut–price framework. Accessed May 4, 2025, https://projects.coin-or.org/Bcp.Google Scholar
  • Department of Defense (2016) Defense casualties analysis system (DCAS) operation freedom’s sentinel (OFS). Accessed May 4, 2025, https://dcas.dmdc.osd.mil/dcas/app/conflictCasualties/ofs.Google Scholar
  • Erkut E, Ingolfsson A, Sim T, Erdogan G (2009) Computational comparison of five maximal covering models for locating ambulances. Geogr. Anal. 41(1):43–65.CrossrefGoogle Scholar
  • Escudero LF, Garín MA, Monge JF, Unzueta A (2018) On preparedness resource allocation planning for natural disaster relief under endogenous uncertainty with time-consistent risk-averse management. Comput. Oper. Res. 98(1):84–102.CrossrefGoogle Scholar
  • Grannan BC, Bastian ND, McLay LA (2015) A maximum expected covering problem for locating and dispatching two classes of military medical evacuation air assets. Optim. Lett. 9(8):1511–1531.CrossrefGoogle Scholar
  • Hellemo L, Barton PI, Tomasgard A (2018) Decision-dependent probabilities in stochastic programs with recourse. Comput. Management Sci. 15(4):369–395.CrossrefGoogle Scholar
  • Homem-de-Mello T, Kong Q, Godoy-Barba R (2022) A simulation optimization approach for the appointment scheduling problem with decision-dependent uncertainties. INFORMS J. Comput. 34(5):2845–2865.LinkGoogle Scholar
  • Jenkins PR, Robbins MJ, Lunday BJ (2018) Examining military medical evacuation dispatching policies utilizing a Markov decision process model of a controlled queueing system. Ann. Oper. Res. 271(1):641–678.CrossrefGoogle Scholar
  • Jenkins PR, Robbins MJ, Lunday BJ (2021) Approximate dynamic programming for military medical evacuation dispatching policies. INFORMS J. Comput. 33(1):2–26.LinkGoogle Scholar
  • Keller J (2018) This is one of the biggest reasons why the deadly ambush in Niger won’t be the last. Accessed September 22, 2025, https://taskandpurpose.com/niger-ambush-medevac-casevac.Google Scholar
  • Keneally SK, Robbins MJ, Lunday BJ (2016) A Markov decision process model for the optimal dispatch of military medical evacuation assets. Health Care Management Sci. 19(1):111–129.CrossrefGoogle Scholar
  • Kepe M (2018) Lives on the line: The A2/AD challenge to combat casualty care. Modern War Institute — Commentary & Analysis, West Point. Accessed September 22, 2025, https://mwi.westpoint.edu/lives-line-a2ad-challenge-combat-casualty-care/.Google Scholar
  • Kılınç M, Sahinidis N (2018) Exploiting integrality in the global optimization of mixed-integer nonlinear programming problems with BARON. Optim. Methods Softw. 33(3):540–562.CrossrefGoogle Scholar
  • Kogan A, Lejeune MA (2014) Threshold Boolean form for joint probabilistic constraints with random technology matrix. Math. Program. 147(1–2):391–427.CrossrefGoogle Scholar
  • Lejeune MA (2012) Pattern-based modeling and solution of probabilistically constrained optimization problems. Oper. Res. 60(6):1356–1372.LinkGoogle Scholar
  • Lejeune MA (2025a) Boolean reformulation method for linear and nonlinear joint chance constraints. Pardalos PM, Prokopyev OA, eds. Encyclopedia of Optimization (Springer, Cham, Switzerland).Google Scholar
  • Lejeune MA (2025b) Stochastic optimization under decision-dependent uncertainty: Overview and new chance-constrained models. SPS Newsletter — The Newsletter of the Stochastic Programming Soc. 4(1):14–18.Google Scholar
  • Lejeune MA, Margot F (2016) Solving chance constrained problems with random technology matrix and stochastic quadratic inequalities. Oper. Res. 64(4):939–957.LinkGoogle Scholar
  • Lejeune MA, Margot F (2018) Aeromedical battlefield evacuation under endogenous uncertainty in casualty delivery times. Management Sci. 64(12):5461–5959.LinkGoogle Scholar
  • Lejeune MA, Prékopa A (2025) Relaxations for probabilistically constrained stochastic programming problems: Review and extensions. Ann. Oper. Res. Forthcoming.Google Scholar
  • Lejeune MA, Margot F, de Oliveira AD (2025) Stochastic optimization model with exogenous and decision-dependent uncertainty for medical evacuation. https://doi.org/10.1287/ijoc.2024.0986.cd, https://github.com/INFORMSJoC/2024.0986.Google Scholar
  • Linde AS (2018) The need for pre-hospital simulation training platforms in battlefield medicine. J. Trauma Rehabilitation 1:1.Google Scholar
  • M*A*S*H (1972) Television series page. Accessed September 22, 2025, https://www.imdb.com/title/tt0068098/.Google Scholar
  • McCormick GP (1976) Computability of global solutions to factorable nonconvex programs: Part I. Convex underestimating problems. Math. Program. 10(1):147–175.CrossrefGoogle Scholar
  • Noyan N, Rudolf G, Lejeune M (2022) Distributionally robust optimization under a decision-dependent ambiguity set with applications to machine scheduling and humanitarian logistics. INFORMS J. Comput. 34(2):729–751.LinkGoogle Scholar
  • Peeta S, Salman F, Gunnec D, Viswanath K (2010) Pre-disaster investment decisions for strengthening a highway network. Comput. Oper. Res. 37(1):1708–1719.CrossrefGoogle Scholar
  • Prékopa A (1995) Stochastic Programming (Kluwer, Boston).CrossrefGoogle Scholar
  • ReVelle C, Hogan K (1989) The maximum reliability location problem and alpha-reliable p-center problem: Derivatives of the probabilistic location set covering problems. Ann. Oper. Res. 18(1):155–173.CrossrefGoogle Scholar
  • Shackelford SA, Del Junco D, Mazuchowski EL, Kotwal RS, Remley MA, Keenan S, Gurney JM (2024) The golden hour of casualty care: Rapid handoff to surgical team is associated with improved survival in war-injured US service members. Ann. Surg. 279(1):1–10.CrossrefGoogle Scholar
  • Sundstrom SC, Blood CG, Matheny SA (1996) The optimal placement of casualty evacuation assets: A linear programming model. Charnes JM, Morrice DJ, Brunner DT, Swain JJ, eds. Proc. 1996 Winter Simulation Conf. (IEEE, Piscataway, NJ), 907–911.CrossrefGoogle 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.