Emergency Drone Deployment and Disposable Defibrillator Allocation: A Modular Capacitated Maximum Covering Location Model

Published Online:https://doi.org/10.1287/msom.2024.1027

References

  • AHA Statistical (2017) Heart disease and stroke statistics: 2017 update. Circulation 135(10):e146–603.Google Scholar
  • Alarcon-Gerbier E, Buscher U (2022) Modular and mobile facility location problems: A systematic review. Comput. Indust. Engrg. 173:108734.CrossrefGoogle Scholar
  • Alsalloum OI, Rand GK (2006) Extensions to emergency vehicle location models. Comput. Oper. Res. 33(9):2725–2743.CrossrefGoogle Scholar
  • Ambulance WF (2025). OHCA registry 2023/2024. Accessed October 14, 2025 https://www.wfa.org.nz/about-us/news/ohcar-20232024.Google Scholar
  • Bansal M, Huang KL, Mehrotra S (2018) Decomposition algorithms for two-stage distributionally robust mixed binary programs. SIAM J. Optim. 28(3):2360–2383.CrossrefGoogle Scholar
  • Batta R, Dolan JM, Krishnamurthy NN (1989) The maximal expected covering location problem: Revisited. Transportation Sci. 23(4):277–287.LinkGoogle Scholar
  • Becker L, Eisenberg M, Fahrenbruch C, Cobb L (1998) Public locations of cardiac arrest: Implications for public access defibrillation. Circulation. 97(21):2106–2109.CrossrefGoogle Scholar
  • Berg DD, Bobrow BJ, Berg RA (2019) Key components of a community response to out-of-hospital cardiac arrest. Nature Rev. Cardiology 16(7):407–416.Google Scholar
  • Bertsimas D, Farias VF, Trichakis N (2011) The price of fairness. Oper. Res. 59(1):17–31.LinkGoogle Scholar
  • Boutilier JJ, Chan TC (2022) Drone network design for cardiac arrest response. Manufacturing Service Oper. Management 24(5):2407–2424.LinkGoogle Scholar
  • Breugem T, Van Wassenhove LN (2022) The price of imposing vertical equity through asymmetric outcome constraints. Management Sci. 68(11):7977–7993.LinkGoogle Scholar
  • Brooks SC, Clegg GR, Bray J, Deakin CD, et al. (2022) Optimizing outcomes after out-of-hospital cardiac arrest with innovative approaches to public-access defibrillation: A scientific statement from the international liaison committee on resuscitation. Circulation 145(13):e776–e801.CrossrefGoogle Scholar
  • Caffrey SL, Willoughby PJ, Pepe PE, Becker LB (2002) Public use of automated external defibrillators. New England J. Medicine 347(16):1242–1247.CrossrefGoogle Scholar
  • Chan TC, Demirtas D, Kwon RH (2016) Optimizing the deployment of public access defibrillators. Management Sci. 62(12):3617–3635.LinkGoogle Scholar
  • Chan TC, Shen ZJM, Siddiq A (2018) Robust defibrillator deployment under cardiac arrest location uncertainty via row-and-column generation. Oper. Res. 66(2):358–379.LinkGoogle Scholar
  • Charles A, Lauras M, Van Wassenhove LN, Dupont L (2016) Designing an efficient humanitarian supply network. J. Oper. Management 47(1):58–70.CrossrefGoogle Scholar
  • Cheng C, Adulyasak Y, Rousseau LM (2021) Robust facility location under disruptions. INFORMS J. Optim. 3(3):298–314.LinkGoogle Scholar
  • Chevaleyre Y, Dunne PE, Endriss U, Lang J, Lemaître M, Maudet N, Padget J, et al. (2006) Issues in multiagent resource allocation. Informatica 30(1):3–31.Google Scholar
  • Church R, ReVelle C (1974) The maximal covering location problem. Papers Regional Sci. 32(1):101–118.CrossrefGoogle Scholar
  • Clinical Audit and Research (2021) Out-of-hospital cardiac arrest registry. Accessed February 18, 2025, https://www.resus.org.nz/assets/OHCA_All_NZ_March_2022_HQ.pdf.Google Scholar
  • Cordeau JF, Furini F, Ljubić I (2019) Benders decomposition for very large scale partial set covering and maximal covering location problems. Eur. J. Oper. Res. 275(3):882–896.CrossrefGoogle Scholar
  • Custodio JE, Lejeune MA (2022) Spatiotemporal data set for out-of-hospital cardiac arrests. INFORMS J. Comput. 34(1):4–10.LinkGoogle Scholar
  • Dai Y, Chao X, Fang SC, Nuttle HL (2006) Capacity allocation with traditional and internet channels. Naval Res. Logist. 53(8):772–787.CrossrefGoogle Scholar
  • Daskin MS (1983) A maximum expected covering location model: Formulation, properties and heuristic solution. Transportation Sci. 17(1):48–70.LinkGoogle Scholar
  • DC Fire & EMS Dept (2016) District of Columbia response time performance measures. Accessed January 1, 2025, https://fems.dc.gov/sites/default/files/dc/sites/fems/FY%202016%20Response%20Time%20Performance%20Measures_0.pdf.Google Scholar
  • De Vries H, Van de Klundert J, Wagelmans AP (2020) The roadside healthcare facility location problem a managerial network design challenge. Production Oper. Management 29(5):1165–1187.CrossrefGoogle Scholar
  • Delage E, Ye Y (2010) Distributionally robust optimization under moment uncertainty with application to data-driven problems. Oper. Res. 58(3):595–612.LinkGoogle Scholar
  • Fredericks A (1980) Congestion in blocking systems—A simple approximation technique. Bell System Tech. J. 59(6):805–827.CrossrefGoogle Scholar
  • Gaisendrees C, Jaeger D, Kalra R, Kosmopoulos M, Harkins K, Marquez A, Hodgson L, et al. (2023) The Minnesota first-responder AED project: Aiming to increase survival in out-of-hospital cardiac arrest. Resuscitation Plus 15:100437.CrossrefGoogle Scholar
  • Gao X, Kong N, Griffin P (2024) Shortening emergency medical response time with joint operations of uncrewed aerial vehicles with ambulances. Manufacturing Service Oper. Management 26(2):447–464.LinkGoogle Scholar
  • Gazani M, Niaki S (2021) The capacitated maximal covering location problem with heterogeneous facilities and vehicles and different setup costs: An effective heuristic approach. Internat. J. Indust. Engrg. Comput. 12(1):79–90.CrossrefGoogle Scholar
  • Goddard J (2024) Ambulance response times in England: An emergency? Accessed January 18, 2025.Google Scholar
  • Gratton M, Lindholm DJ, Campbell JP (1999) Public-access defibrillation: Where do we place the aeds? Prehospital Emergency Care 3(4):303–305.CrossrefGoogle Scholar
  • Guo L, Wu X (2018) Capacity sharing between competitors. Management Sci. 64(80):3554–3573.LinkGoogle Scholar
  • Hanasusanto GA, Roitch V, Kuhn D, Wiesemann W (2017) Ambiguous joint chance constraints under mean and dispersion information. Oper. Res. 65(3):751–767.LinkGoogle Scholar
  • HRSA (2007) Service area overlap: Policy and process. Accessed June 1, 2024, https://bphc.hrsa.gov/sites/default/files/bphc/compliance/scopemanual.pdf.Google Scholar
  • Hua C, Swersey AJ (2022) Cross-trained fire-medics respond to medical calls and fire incidents: A fast algorithm for a three-state spatial queuing problem. Manufacturing Service Oper. Management 24(6):3177–3192.LinkGoogle Scholar
  • Jia H, Ordóñez F, Dessouky M (2007) A modeling framework for facility location of medical services for large-scale emergencies. IIE Trans. 39(1):41–55.CrossrefGoogle Scholar
  • Kuhn D, Shafiee S, Wiesemann W (2025) Distributionally robust optimization. Acta Numerics 34:579–804.CrossrefGoogle Scholar
  • Larsen MP, Eisenberg MS, Cummins RO, Hallstrom AP (1993) Predicting survival from out-of-hospital cardiac arrest: A graphic model. Ann. Emergency Medicine 22(11):1652–1658.CrossrefGoogle Scholar
  • Lejeune MA, Ma W (2025) Drone-delivery network for opioid overdose: Nonlinear integer queueing-optimization models and methods. Oper. Res. 73(1):86–108.LinkGoogle Scholar
  • Lejeune MA, Margot F (2025) Response time minimization for cardiac arrests. Production Oper. Management 34(9):2618–2640.CrossrefGoogle Scholar
  • Li AA, Whitt W (2014) Approximate blocking probabilities in loss models with independence and distribution assumptions relaxed. Performance Evaluation 80:82–101.CrossrefGoogle Scholar
  • Li H, Delage E, Zhu N, Pinedo M, Ma S (2024) Distributional robustness and inequity mitigation in disaster preparedness of humanitarian operations. Manufacturing Service Oper. Management 26(1):197–214.LinkGoogle Scholar
  • Li J, Huang Y, Li Y-F, Wang S (2023) Redundancy allocation under state-dependent distributional uncertainty of component lifetimes. Production Oper. Management 32(3):930–950.Google Scholar
  • Liang J, Lyu G, Teo CP, Gao Z (2023) Online passenger flow control in metro lines. Oper. Res.LinkGoogle Scholar
  • Ma Y, Wang T, Zheng H (2022) On fairness and efficiency in nonprofit operations: Dynamic resource allocations. Production Oper. Management 32(6):1778–1792.CrossrefGoogle Scholar
  • McLay LA (2009) A maximum expected covering location model with two types of servers. IIE Trans. 41(8):730–741.CrossrefGoogle Scholar
  • Meier JF, Clausen U (2018) Solving single allocation hub location problems on Euclidean data. Transportation Sci. 52(5):1141–1155.LinkGoogle Scholar
  • Mell HK, Sayre MR (2008) Public access defibrillators and fire extinguishers: Are comparisons reasonable? Progress Cardiovascular Disease 51(3):204–212.CrossrefGoogle Scholar
  • Nishiyama C, Kiguchi T, Okubo M, Alihodžić H, Al-Araji R, Baldi E, Beganton F, et al. (2023) Three-year trends in out-of-hospital cardiac arrest across the world: Second report from the international liaison committee on resuscitation (ILCOR). Resuscitation 186:109757.CrossrefGoogle Scholar
  • Ono Y, Hayakawa M, Iijima H, Maekawa K, Kodate A, Sadamoto Y, Mizugaki A, et al. (2016) The response time threshold for predicting favourable neurological outcomes in patients with bystander-witnessed out-of-hospital cardiac arrest. Resuscitation 107:65–70.CrossrefGoogle Scholar
  • Pirkul H, Schilling DA (1991) The maximal covering location problem with capacities on total workload. Management Sci. 37(2):233–248.LinkGoogle Scholar
  • Pot A, Bhulai S, Koole G (2008) A simple staffing method for multiskill call centers. Manufacturing Service Oper. Management 10(3):421–428.LinkGoogle Scholar
  • Queensland Ambulance Service (2021) 2021 annual report. Accessed May 10, 2025, https://www.ambulance.qld.gov.au/__data/assets/pdf_file/0019/221743/QAS_Cardiac_Annual_Report_2021.pdf.Google Scholar
  • Rahimian H, Mehrotra S (2019) Distributionally robust optimization: A review. Preprint, submitted August 13, https://arxiv.org/abs/1908.05659.Google Scholar
  • Schierbeck S, Nord A, Svensson L, Ringh M, Nordberg P, Hollenberg J, Lundgren P, et al. (2023) Drone delivery of automated external defibrillators compared with ambulance arrival in real-life suspected out-of-hospital cardiac arrests: A prospective observational study in Sweden. Lancet Digital Health 5(12):e862–e871.CrossrefGoogle Scholar
  • Schuetz HJ, Kolisch R (2012) Approximate dynamic programming for capacity allocation in the service industry. Eur. J. Oper. Res. 218(1):239–250.CrossrefGoogle Scholar
  • Shehadeh KS (2022) Distributionally robust optimization approaches for a stochastic mobile facility fleet sizing, routing, and scheduling problem. Transportation Sci. 57(1):197–229.Google Scholar
  • Shin J, Marla L, Boutilier J (2022) Heterogeneous facility location under coordination and collaboration: The case of ambulance-bystander-drone coordination. Preprint, submitted August 22, https://doi.org/10.2139/ssrn.3519243.Google Scholar
  • Shulman A (1991) An algorithm for solving dynamic capacitated plant location problems with discrete expansion sizes. Oper. Res. 39(3):423–436.LinkGoogle Scholar
  • Sitompul C, Aghezzaf EH, Dullaert W, Landeghem HV (2008) Safety stock placement problem in capacitated supply chains. Internat. J. Production Res. 46(17):4709–4727.CrossrefGoogle Scholar
  • Song JS, van Houtum GJ, Van Mieghem JA (2020) Capacity and inventory management: Review, trends, and projections. Manufacturing Service Oper. Management 22(1):36–46.LinkGoogle Scholar
  • Sudden Cardiac Arrest Foundation (2025) Latest statistics on sudden cardiac arrest. Accessed August 20, 2025, https://www.sca-aware.org/about-sudden-cardiac-arrest/latest-statistics.Google Scholar
  • Sun CL, Demirtas D, Brooks SC, Morrison LJ, Chan TC (2016) Overcoming spatial and temporal barriers to public access defibrillators via optimization. J. Amer. College Cardiology 68(8):836–845.CrossrefGoogle Scholar
  • Toregas C, Swain R, ReVelle C, Bergman L (1971) The location of emergency service facilities. Oper. Res. 19(6):1363–1373.LinkGoogle Scholar
  • Turley A, Bone G, Garcia L, de Belder M, Gedney J (2005) Cardiopulmonary resuscitation training: The need for continued education and training. Critical Care 9(1):1–2.Google Scholar
  • Valenzuela TD, Roe DJ, Nichol G, Clark LL, et al. (2000) Outcomes of rapid defibrillation by security officers after cardiac arrest in casinos. New England J. Medicine 343(17):1206–1209.CrossrefGoogle Scholar
  • van den Berg PL, Henderson SG, Jagtenberg CJ, Li H (2024) Modeling the impact of community first responders. Management Sci. 71(2):992–1008.Google Scholar
  • van Eekelen WJ, den Hertog D, van Leeuwaarden JS (2025) Distributionally robust appointment scheduling that can deal with independent service times. Production Oper. Management 34(6):1458–1476.CrossrefGoogle Scholar
  • Vatsa AK, Jayaswal S (2021) Capacitated multi-period maximal covering location problem with server uncertainty. Eur. J. Oper. Res. 289(3):1107–1126.CrossrefGoogle Scholar
  • Wang S, Chen Z, Liu T (2020) Distributionally robust hub location. Transportation Sci. 54(5):1189–1210.LinkGoogle Scholar
  • Weisfeldt ML, Sitlani CM, Ornato JP, et al. (2010) Survival after application of automatic external defibrillators before arrival of the emergency medical system: Evaluation in the resuscitation outcomes consortium population of 21 million. J. Amer. College Cardiology 55(16):1713–1720.CrossrefGoogle Scholar
  • Wiesemann W, Kuhn D, Sim M (2014) Distributionally robust convex optimization. Oper. Res. 62(6):1358–1376.LinkGoogle Scholar
  • Yin P, Mu L (2012) Modular capacitated maximal covering location problem for the optimal siting of emergency vehicles. Appl. Geography 34:247–254.CrossrefGoogle Scholar
  • Zhu M, Liu Z, Li J, Zhu SX (2020) Electric vehicle battery capacity allocation and recycling with downstream competition. Eur. J. Oper. Res. 283(1):365–379.CrossrefGoogle Scholar
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