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Response Areas for Two Emergency Units

Author

Listed:
  • Grace M. Carter

    (The New York City-Rand Institute, New York, New York)

  • Jan M. Chaiken

    (The New York City-Rand Institute, New York, New York)

  • Edward Ignall

    (Columbia University and The New York City-Rand Institute, New York, New York)

Abstract

This paper gives a model in which two urban emergency service units (such as fire engines or ambulances) cooperate in responding to alarms or calls from the public in a specified region of a city. Given the home locations of the units and the spatial distribution of alarm rates, it is possible to specify which unit should respond to each alarm by defining a response area for each unit. The average response time to alarms and the workload of each unit are calculated as functions of the boundary that separates their response areas. The boundaries that minimize average response time and the ones that equalize workload are determined. Some boundaries can be dominated, in the sense that another boundary improves both workload balance and response time. The set of undominated boundaries is found.

Suggested Citation

  • Grace M. Carter & Jan M. Chaiken & Edward Ignall, 1972. "Response Areas for Two Emergency Units," Operations Research, INFORMS, vol. 20(3), pages 571-594, June.
    • Handle: RePEc:inm:oropre:v:20:y:1972:i:3:p:571-594
    DOI: 10.1287/opre.20.3.571
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    Cited by:

    1. Phillip R. Jenkins & Matthew J. Robbins & Brian J. Lunday, 2021. "Approximate Dynamic Programming for Military Medical Evacuation Dispatching Policies," INFORMS Journal on Computing, INFORMS, vol. 33(1), pages 2-26, January.
    2. Linda V. Green & Peter J. Kolesar, 2004. "ANNIVERSARY ARTICLE: Improving Emergency Responsiveness with Management Science," Management Science, INFORMS, vol. 50(8), pages 1001-1014, August.
    3. Rettke, Aaron J. & Robbins, Matthew J. & Lunday, Brian J., 2016. "Approximate dynamic programming for the dispatch of military medical evacuation assets," European Journal of Operational Research, Elsevier, vol. 254(3), pages 824-839.
    4. Phillip R. Jenkins & Matthew J. Robbins & Brian J. Lunday, 2018. "Examining military medical evacuation dispatching policies utilizing a Markov decision process model of a controlled queueing system," Annals of Operations Research, Springer, vol. 271(2), pages 641-678, December.
    5. Bertsimas, Dimitris & Ng, Yeesian, 2019. "Robust and stochastic formulations for ambulance deployment and dispatch," European Journal of Operational Research, Elsevier, vol. 279(2), pages 557-571.
    6. Bélanger, V. & Lanzarone, E. & Nicoletta, V. & Ruiz, A. & Soriano, P., 2020. "A recursive simulation-optimization framework for the ambulance location and dispatching problem," European Journal of Operational Research, Elsevier, vol. 286(2), pages 713-725.
    7. P. Daniel Wright & Matthew J. Liberatore & Robert L. Nydick, 2006. "A Survey of Operations Research Models and Applications in Homeland Security," Interfaces, INFORMS, vol. 36(6), pages 514-529, December.
    8. Richard Charles Larson, 2002. "Public Sector Operations Research: A Personal Journey," Operations Research, INFORMS, vol. 50(1), pages 135-145, February.
    9. Laura A. McLay & Maria E. Mayorga, 2013. "A Dispatching Model for Server-to-Customer Systems That Balances Efficiency and Equity," Manufacturing & Service Operations Management, INFORMS, vol. 15(2), pages 205-220, May.
    10. Wang, Qingyi & Reed, Ashley & Nie, Xiaofeng, 2022. "Joint initial dispatching of official responders and registered volunteers during catastrophic mass-casualty incidents," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 159(C).
    11. Mahmut Parlar, 2023. "Model Development with Maple in PhD-Level Management Science Courses: A Personal Account," SN Operations Research Forum, Springer, vol. 4(1), pages 1-24, March.
    12. Bélanger, V. & Ruiz, A. & Soriano, P., 2019. "Recent optimization models and trends in location, relocation, and dispatching of emergency medical vehicles," European Journal of Operational Research, Elsevier, vol. 272(1), pages 1-23.
    13. Susana Baptista & Rui Oliveira, 2012. "A case study on the application of an approximated hypercube model to emergency medical systems management," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 20(4), pages 559-581, December.
    14. Liu, Han & Hua, Cheng & Lei, Chao, 2021. "Planning for time-varying volunteer firefighter systems under probabilistic service disruptions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 154(C).
    15. S Lee, 2011. "The role of preparedness in ambulance dispatching," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(10), pages 1888-1897, October.
    16. Seokcheon Lee, 2017. "A new preparedness policy for EMS logistics," Health Care Management Science, Springer, vol. 20(1), pages 105-114, March.
    17. Drent, Collin & Keizer, Minou Olde & Houtum, Geert-Jan van, 2020. "Dynamic dispatching and repositioning policies for fast-response service networks," European Journal of Operational Research, Elsevier, vol. 285(2), pages 583-598.
    18. Jagtenberg, C.J. & van den Berg, P.L. & van der Mei, R.D., 2017. "Benchmarking online dispatch algorithms for Emergency Medical Services," European Journal of Operational Research, Elsevier, vol. 258(2), pages 715-725.
    19. T Andersson & P Värbrand, 2007. "Decision support tools for ambulance dispatch and relocation," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(2), pages 195-201, February.
    20. C. J. Jagtenberg & S. Bhulai & R. D. Mei, 2017. "Dynamic ambulance dispatching: is the closest-idle policy always optimal?," Health Care Management Science, Springer, vol. 20(4), pages 517-531, December.
    21. Sardar Ansari & Laura Albert McLay & Maria E. Mayorga, 2017. "A Maximum Expected Covering Problem for District Design," Transportation Science, INFORMS, vol. 51(1), pages 376-390, February.

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