Computational Study of Emergency Service System Reengineering Under Generalized Disutility

  • Marek KvetEmail author
  • Jaroslav Janáček
  • Michal Kvet
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 966)


Emergency medical service system structure is determined by deployment of limited number of the service providing centers. The objective of the designer is to minimize the total discomfort of all system users. Thus, the problem often takes the form of the weighted p-median problem. Since population and demands for service change in time and space, current service center deployment may not meet the requirements of the users and service providers neither. We suggest and discuss a mathematical model for system reengineering under the generalized disutility. Formulation of the generalized disutility follows from the idea that the individual user’s disutility is caused by positions of more than one located service center. Generalized disutility enables to model the system performance more realistically. It enables to take into account also such situations in which the nearest service center may be temporarily unavailable due to satisfying another demand. This approach represents an extension of our previous research, in which only the nearest center was taken as a source of individual user’s demand satisfaction.


Emergency medical service System reengineering Generalized disutility Radial formulation 



This work was supported by the research grants VEGA 1/0342/18 “Optimal dimensioning of service systems”, VEGA 1/0463/16 “Economically efficient charging infrastructure deployment for electric vehicles in smart cities and communities”, and APVV-15-0179 “Reliability of emergency systems on infrastructure with uncertain functionality of critical elements”.


  1. 1.
    Avella, P., Sassano, A., Vasil’ev, I.: Computational study of large scale p-median problems. Math. Program. 109(1), 89–114 (2007)MathSciNetCrossRefGoogle Scholar
  2. 2.
    Current, J., Daskin, M., Schilling, D.: Discrete network location models. In: Drezner, Z., et al. (eds.) Facility Location. Applications and Theory, pp. 81–118. Springer, Berlin (2002)CrossRefGoogle Scholar
  3. 3.
    Doerner, K.F., et al.: Heuristic solution of an extended double-coverage ambulance location problem for Austria. CEJOR 13(4), 325–340 (2005)zbMATHGoogle Scholar
  4. 4.
    Elloumi, S., Labbé, M., Pochet, Y.: A new formulation and resolution method for the p-center problem. INFORMS J. Comput. 16, 84–94 (2004)MathSciNetCrossRefGoogle Scholar
  5. 5.
    García, S., Labbé, M., Marín, A.: Solving large p-median problems with a radius formulation. INFORMS J. Comput. 23(4), 546–556 (2011)MathSciNetCrossRefGoogle Scholar
  6. 6.
    Ingolfsson, A., Budge, S., Erkut, E.: Optimal ambulance location with random delays and travel times. Health Care Manage. Sci. 11(3), 262–274 (2008)CrossRefGoogle Scholar
  7. 7.
    Janáček, J.: Approximate covering models of location problems. In Lecture Notes in Management Science: Proceedings of the 1st International Conference ICAOR, Yerevan, pp. 53–61 (2008)Google Scholar
  8. 8.
    Janáček, J., Kvet, M.: Public service system design with disutility relevance estimation. In Mathematical Methods in Economics, Jihlava, pp. 332–337 (2013)Google Scholar
  9. 9.
    Jankovič P.: Calculating reduction coefficients for optimization of emergency service system using microscopic simulation model. In: In 17th International Symposium on Computational Intelligence and Informatics, Budapest, pp. 163–167 (2016)Google Scholar
  10. 10.
    Jánošíková, Ľ.: Emergency medical service planning. Commun. Sci. Lett. Univ. Žilina 9(2), 64–68 (2007)Google Scholar
  11. 11.
    Kvet, M.: Computational study of radial approach to public service system design with generalized utility. In: Proceedings of the 10th International Conference on Digital Technologies, pp. 198–208. IEEE (2014)Google Scholar
  12. 12.
    Kvet, M., Janáček, J.: Radiálny prístup na zlepšenie existujúceho záchranného systému. In: Optimalizační úlohy v dopravních a logistických systémech a SW podpora rozhodování v inteligentních dopravních systémech, Praha, pp. 11–25 (2016)Google Scholar
  13. 13.
    Kvet, M., Janáček, J.: Reengineering of the emergency service system under generalized disutility. In: 7th International Conference on Operations Research and Enterprise Systems, ICORES 2018, Madeira, pp. 85–93 (2018)Google Scholar
  14. 14.
    Snyder, L.V., Daskin, M.S.: Reliability models for facility location; the expected failure cost case. Transp. Sci. 39(3), 400–416 (2005)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Faculty of Management Science and InformaticsUniversity of ŽilinaŽilinaSlovakia

Personalised recommendations