Advertisement

An Optimization Model to Rationalize Public Service Facilities

  • M. Cavola
  • A. DiglioEmail author
  • C. Piccolo
Chapter
Part of the AIRO Springer Series book series (AIROSS, volume 1)

Abstract

Facility Location Models (FLMs) have been widely applied in the context of both private and public sector, to decide the best configuration of new facilities to be located in a given area. In the last years, due to the general interest to reduce costs and improve efficiency, several works focused on problems aimed at modifying the territorial configuration of existing facilities, in terms of number, position and/or capacities, etc. In this work, we propose a new mathematical model to support territorial re-organization decisions in non-competitive contexts. The model assumes the presence of a set of facilities providing different types of services to users (multi-type facilities) and explores the possibility to improve the efficiency of the system by implementing different rationalization actions; i.e., facility closure, service closure, capacity reallocation among services at a given facility. The model aims at finding a trade-off solution between the service efficiency and the need of ensuring a given accessibility level to users. It has been tested on a set of randomly generated instances, to show that a good range of problems can be solved to optimality through the use of a commercial solver (CPLEX).

Keywords

Facility location models Territorial re-organization Public sector 

References

  1. 1.
    Eiselt, H.A., Marianov, V. (eds.): Foundations of Location Analysis. Springer, New York (2011)zbMATHGoogle Scholar
  2. 2.
    Laporte, G., Nickel, S., Saldanha-Da-Gama, F. (eds.): Location Science. Springer, Berlin (2014)Google Scholar
  3. 3.
    Erkut, E., Karagiannidis, A., Perkoulidis, G., Tjandra, S.A.: A multicriteria facility location model for municipal solid waste management in North Greece. Eur. J. Oper. Res. 187(3), 1402–1421 (2008)MathSciNetCrossRefGoogle Scholar
  4. 4.
    Melo, M.T., Nickel, S., Saldanha-Da-Gama, F.: Facility location and supply chain management—a review. Eur. J. Oper. Res. 196(2), 401–412 (2009)MathSciNetCrossRefGoogle Scholar
  5. 5.
    Daskin, M.S.: Network and Discrete Location: Models, Algorithms, and Applications. Wiley (2011)Google Scholar
  6. 6.
    Farahani, R.Z., Hekmatfar, M., Arabani, A.B., Nikbakhsh, E.: Hub location problems: a review of models, classification, solution techniques, and applications. Comput. Ind. Eng. 64(4), 1096–1109 (2013)CrossRefGoogle Scholar
  7. 7.
    Sterle, C., Sforza, A., Amideo, A.E.: Multi-period location of flow intercepting portable facilities of an intelligent transportation system. Socio-Econ. Plan. Sci. 53, 4–13 (2016)CrossRefGoogle Scholar
  8. 8.
    Marianov, V., Serra, D.: Location problems in the public sector. Facil. Locat. Appl. Theor. 1, 119–150 (2002)MathSciNetCrossRefGoogle Scholar
  9. 9.
    Araya, F., Dell, R., Donoso, P., Marianov, V., Martínez, F., Weintraub, A.: Optimizing location and size of rural schools in Chile. Int. Trans. Oper. Res. 19(5), 695–710 (2012)MathSciNetCrossRefGoogle Scholar
  10. 10.
    Marsh, M.T., Schilling, D.A.: Equity measurement in facility location analysis: a review and framework. Eur. J. Oper. Res. 74(1), 1–17 (1994)CrossRefGoogle Scholar
  11. 11.
    Barbati, M., Piccolo, C.: Equality measures properties for location problems. Optim. Lett. 10(5), 903–920 (2016)MathSciNetCrossRefGoogle Scholar
  12. 12.
    Bruno, G., Genovese, A., Piccolo, C.: Capacity management in public service facility networks: a model, computational tests and a case study. Optim. Lett. 10(5), 975–995 (2016)MathSciNetCrossRefGoogle Scholar
  13. 13.
    Bruno, G., Genovese, A., Piccolo, C.: Territorial amalgamation decisions in local government: models and a case study from Italy. Socio-Econ. Plan. Sci. 57, 61–72 (2017)CrossRefGoogle Scholar
  14. 14.
    Wilhelm, W., Han, X., Lee, C.: Computational comparison of two formulations for dynamic supply chain reconfiguration with capacity expansion and contraction. Comput. Oper. Res. 40(10), 2340–2356 (2013)CrossRefGoogle Scholar
  15. 15.
    Sonmez, A.D., Lim, G.J.: A decomposition approach for facility location and relocation problem with uncertain number of future facilities. Eur. J. Oper. Res. 218(2), 327–338 (2012)MathSciNetCrossRefGoogle Scholar
  16. 16.
    Wang, Q., Batta, R., Bhadury, J., Rump, C.M.: Budget constrained location problem with opening and closing of facilities. Comput. Oper. Res. 30(13), 2047–2069 (2003)MathSciNetCrossRefGoogle Scholar
  17. 17.
    ReVelle, C., Murray, A.T., Serra, D.: Location models for ceding market share and shrinking services. Omega 35(5), 533–540 (2007)CrossRefGoogle Scholar
  18. 18.
    Bruno, G., Esposito, E., Genovese, A., Piccolo, C.: Institutions and facility mergers in the Italian education system: Models and case studies. Socio-Econ. Plan. Sci. 53, 23–32 (2016)CrossRefGoogle Scholar
  19. 19.
    Guerriero, F., Miglionico, G., Olivito, F.: Location and reorganization problems: the Calabrian health care system case. Eur. J. Oper. Res. 250(3), 939–954 (2016)MathSciNetCrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Department of Industrial EngineeringUniversity of Naples Federico IINaplesItaly

Personalised recommendations