IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v181y2010i1p559-58910.1007-s10479-010-0787-x.html
   My bibliography  Save this article

Alternate risk measures for emergency medical service system design

Author

Listed:
  • Nilay Noyan

Abstract

The stochastic nature of emergency service requests and the unavailability of emergency vehicles when requested to serve demands are critical issues in constructing valid models representing real life emergency medical service (EMS) systems. We consider an EMS system design problem with stochastic demand and locate the emergency response facilities and vehicles in order to ensure target levels of coverage, which are quantified using risk measures on random unmet demand. The target service levels for each demand site and also for the entire service area are specified. In order to increase the possibility of representing a wider range of risk preferences we develop two types of stochastic optimization models involving alternate risk measures. The first type of the model includes integrated chance constraints (ICCs ), whereas the second type incorporates ICCs and a stochastic dominance constraint. We develop solution methods for the proposed single-stage stochastic optimization problems and present extensive numerical results demonstrating their computational effectiveness. Copyright Springer Science+Business Media, LLC 2010

Suggested Citation

  • Nilay Noyan, 2010. "Alternate risk measures for emergency medical service system design," Annals of Operations Research, Springer, vol. 181(1), pages 559-589, December.
    • Handle: RePEc:spr:annopr:v:181:y:2010:i:1:p:559-589:10.1007/s10479-010-0787-x
    DOI: 10.1007/s10479-010-0787-x
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10479-010-0787-x
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10479-010-0787-x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Mark S. Daskin, 1983. "A Maximum Expected Covering Location Model: Formulation, Properties and Heuristic Solution," Transportation Science, INFORMS, vol. 17(1), pages 48-70, February.
    2. Beraldi, P. & Bruni, M. E. & Conforti, D., 2004. "Designing robust emergency medical service via stochastic programming," European Journal of Operational Research, Elsevier, vol. 158(1), pages 183-193, October.
    3. Rajan Batta & June M. Dolan & Nirup N. Krishnamurthy, 1989. "The Maximal Expected Covering Location Problem: Revisited," Transportation Science, INFORMS, vol. 23(4), pages 277-287, November.
    4. Marsh, Michael T. & Schilling, David A., 1994. "Equity measurement in facility location analysis: A review and framework," European Journal of Operational Research, Elsevier, vol. 74(1), pages 1-17, April.
    5. Owen, Susan Hesse & Daskin, Mark S., 1998. "Strategic facility location: A review," European Journal of Operational Research, Elsevier, vol. 111(3), pages 423-447, December.
    6. Armann Ingolfsson & Susan Budge & Erhan Erkut, 2008. "Optimal ambulance location with random delays and travel times," Health Care Management Science, Springer, vol. 11(3), pages 262-274, September.
    7. Darinka Dentcheva & Andrzej Ruszczynski, 2004. "Optimization Under First Order Stochastic Dominance Constraints," GE, Growth, Math methods 0403002, University Library of Munich, Germany, revised 07 Aug 2005.
    8. Haim Levy, 1992. "Stochastic Dominance and Expected Utility: Survey and Analysis," Management Science, INFORMS, vol. 38(4), pages 555-593, April.
    9. Erhan Erkut & Armann Ingolfsson & Güneş Erdoğan, 2008. "Ambulance location for maximum survival," Naval Research Logistics (NRL), John Wiley & Sons, vol. 55(1), pages 42-58, February.
    10. Noyan, Nilay & Prekopa, Andras, 2006. "A variant of the Hungarian inventory control model," International Journal of Production Economics, Elsevier, vol. 103(2), pages 784-797, October.
    11. Brotcorne, Luce & Laporte, Gilbert & Semet, Frederic, 2003. "Ambulance location and relocation models," European Journal of Operational Research, Elsevier, vol. 147(3), pages 451-463, June.
    12. Willem Haneveld & Maarten Vlerk, 2006. "Integrated Chance Constraints: Reduced Forms and an Algorithm," Computational Management Science, Springer, vol. 3(4), pages 245-269, September.
    13. Beraldi, P. & Bruni, M.E., 2009. "A probabilistic model applied to emergency service vehicle location," European Journal of Operational Research, Elsevier, vol. 196(1), pages 323-331, July.
    14. Hadar, Josef & Russell, William R, 1969. "Rules for Ordering Uncertain Prospects," American Economic Review, American Economic Association, vol. 59(1), pages 25-34, March.
    15. Felder, Stefan & Brinkmann, Henrik, 2002. "Spatial allocation of emergency medical services: minimising the death rate or providing equal access?," Regional Science and Urban Economics, Elsevier, vol. 32(1), pages 27-45, January.
    16. Charles ReVelle & Kathleen Hogan, 1989. "The Maximum Availability Location Problem," Transportation Science, INFORMS, vol. 23(3), pages 192-200, August.
    17. Michael O. Ball & Feng L. Lin, 1993. "A Reliability Model Applied to Emergency Service Vehicle Location," Operations Research, INFORMS, vol. 41(1), pages 18-36, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Semih Yalçındağ & Seda Baş Güre & Giuliana Carello & Ettore Lanzarone, 2020. "A stochastic risk-averse framework for blood donation appointment scheduling under uncertain donor arrivals," Health Care Management Science, Springer, vol. 23(4), pages 535-555, December.
    2. Sondes Hammami & Aida Jebali, 2021. "Designing modular capacitated emergency medical service using information on ambulance trip," Operational Research, Springer, vol. 21(3), pages 1723-1742, September.
    3. Roberto Aringhieri & Giuliana Carello & Daniela Morale, 2016. "Supporting decision making to improve the performance of an Italian Emergency Medical Service," Annals of Operations Research, Springer, vol. 236(1), pages 131-148, January.
    4. Nilay Noyan & Burcu Balcik & Semih Atakan, 2016. "A Stochastic Optimization Model for Designing Last Mile Relief Networks," Transportation Science, INFORMS, vol. 50(3), pages 1092-1113, August.
    5. Gang Kou & Wenshuai Wu, 2014. "Multi-criteria decision analysis for emergency medical service assessment," Annals of Operations Research, Springer, vol. 223(1), pages 239-254, December.
    6. Nilay Noyan & Gábor Rudolf, 2013. "Optimization with Multivariate Conditional Value-at-Risk Constraints," Operations Research, INFORMS, vol. 61(4), pages 990-1013, August.
    7. Zhi-Hai Zhang & Kang Li, 2015. "A novel probabilistic formulation for locating and sizing emergency medical service stations," Annals of Operations Research, Springer, vol. 229(1), pages 813-835, June.
    8. Nilay Noyan & Gökçe Kahvecioğlu, 2018. "Stochastic last mile relief network design with resource reallocation," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 40(1), pages 187-231, January.
    9. Ibrahim Çapar & Sharif H Melouk & Burcu B Keskin, 2017. "Alternative metrics to measure EMS system performance," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(7), pages 792-808, July.
    10. Nelas, José & Dias, Joana, 2020. "Optimal Emergency Vehicles Location: An approach considering the hierarchy and substitutability of resources," European Journal of Operational Research, Elsevier, vol. 287(2), pages 583-599.
    11. Rania Boujemaa & Aida Jebali & Sondes Hammami & Angel Ruiz & Hanen Bouchriha, 2018. "A stochastic approach for designing two-tiered emergency medical service systems," Flexible Services and Manufacturing Journal, Springer, vol. 30(1), pages 123-152, June.
    12. Liu, Kanglin & Li, Qiaofeng & Zhang, Zhi-Hai, 2019. "Distributionally robust optimization of an emergency medical service station location and sizing problem with joint chance constraints," Transportation Research Part B: Methodological, Elsevier, vol. 119(C), pages 79-101.
    13. Gutjahr, Walter J. & Fischer, Sophie, 2018. "Equity and deprivation costs in humanitarian logistics," European Journal of Operational Research, Elsevier, vol. 270(1), pages 185-197.
    14. Soovin Yoon & Laura A. Albert & Veronica M. White, 2021. "A Stochastic Programming Approach for Locating and Dispatching Two Types of Ambulances," Transportation Science, INFORMS, vol. 55(2), pages 275-296, March.
    15. Wang, Wei & Wu, Shining & Wang, Shuaian & Zhen, Lu & Qu, Xiaobo, 2021. "Emergency facility location problems in logistics: Status and perspectives," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 154(C).
    16. Roberto Aringhieri & Giuliana Carello & Daniela Morale, 2016. "Supporting decision making to improve the performance of an Italian Emergency Medical Service," Annals of Operations Research, Springer, vol. 236(1), pages 131-148, January.
    17. Carlos García-Alonso & Leonor Pérez-Naranjo & Juan Fernández-Caballero, 2014. "Multiobjective evolutionary algorithms to identify highly autocorrelated areas: the case of spatial distribution in financially compromised farms," Annals of Operations Research, Springer, vol. 219(1), pages 187-202, August.
    18. Liu, Kanglin & Zhang, Hengliang & Zhang, Zhi-Hai, 2021. "The efficiency, equity and effectiveness of location strategies in humanitarian logistics: A robust chance-constrained approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 156(C).
    19. Liu, Kanglin & Liu, Changchun & Xiang, Xi & Tian, Zhili, 2023. "Testing facility location and dynamic capacity planning for pandemics with demand uncertainty," European Journal of Operational Research, Elsevier, vol. 304(1), pages 150-168.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. 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.
    3. Wang, Wei & Wu, Shining & Wang, Shuaian & Zhen, Lu & Qu, Xiaobo, 2021. "Emergency facility location problems in logistics: Status and perspectives," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 154(C).
    4. 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.
    5. Sorensen, Paul & Church, Richard, 2010. "Integrating expected coverage and local reliability for emergency medical services location problems," Socio-Economic Planning Sciences, Elsevier, vol. 44(1), pages 8-18, March.
    6. Beraldi, P. & Bruni, M.E., 2009. "A probabilistic model applied to emergency service vehicle location," European Journal of Operational Research, Elsevier, vol. 196(1), pages 323-331, July.
    7. Zhi-Hai Zhang & Kang Li, 2015. "A novel probabilistic formulation for locating and sizing emergency medical service stations," Annals of Operations Research, Springer, vol. 229(1), pages 813-835, June.
    8. Shariat-Mohaymany, Afshin & Babaei, Mohsen & Moadi, Saeed & Amiripour, Sayyed Mahdi, 2012. "Linear upper-bound unavailability set covering models for locating ambulances: Application to Tehran rural roads," European Journal of Operational Research, Elsevier, vol. 221(1), pages 263-272.
    9. Sunarin Chanta & Maria Mayorga & Laura McLay, 2014. "Improving emergency service in rural areas: a bi-objective covering location model for EMS systems," Annals of Operations Research, Springer, vol. 221(1), pages 133-159, October.
    10. Xueping Li & Zhaoxia Zhao & Xiaoyan Zhu & Tami Wyatt, 2011. "Covering models and optimization techniques for emergency response facility location and planning: a review," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 74(3), pages 281-310, December.
    11. Rajagopalan, Hari K. & Saydam, Cem, 2009. "A minimum expected response model: Formulation, heuristic solution, and application," Socio-Economic Planning Sciences, Elsevier, vol. 43(4), pages 253-262, December.
    12. Cheng, Yung-Hsiang & Liang, Zheng-Xian, 2014. "A strategic planning model for the railway system accident rescue problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 69(C), pages 75-96.
    13. Mahdi Moeini & Zied Jemai & Evren Sahin, 2015. "Location and relocation problems in the context of the emergency medical service systems: a case study," 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. 23(3), pages 641-658, September.
    14. Nelas, José & Dias, Joana, 2020. "Optimal Emergency Vehicles Location: An approach considering the hierarchy and substitutability of resources," European Journal of Operational Research, Elsevier, vol. 287(2), pages 583-599.
    15. Boyacı, Burak & Geroliminis, Nikolas, 2015. "Approximation methods for large-scale spatial queueing systems," Transportation Research Part B: Methodological, Elsevier, vol. 74(C), pages 151-181.
    16. 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.
    17. Geroliminis, Nikolas & Karlaftis, Matthew G. & Skabardonis, Alexander, 2009. "A spatial queuing model for the emergency vehicle districting and location problem," Transportation Research Part B: Methodological, Elsevier, vol. 43(7), pages 798-811, August.
    18. Rajagopalan, Hari K. & Vergara, F. Elizabeth & Saydam, Cem & Xiao, Jing, 2007. "Developing effective meta-heuristics for a probabilistic location model via experimental design," European Journal of Operational Research, Elsevier, vol. 177(1), pages 83-101, February.
    19. Soovin Yoon & Laura A. Albert & Veronica M. White, 2021. "A Stochastic Programming Approach for Locating and Dispatching Two Types of Ambulances," Transportation Science, INFORMS, vol. 55(2), pages 275-296, March.
    20. Shayesta Wajid & N. Nezamuddin, 2023. "Optimizing emergency services for road safety using a decomposition method: a case study of Delhi," OPSEARCH, Springer;Operational Research Society of India, vol. 60(1), pages 155-173, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:annopr:v:181:y:2010:i:1:p:559-589:10.1007/s10479-010-0787-x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.