IDEAS home Printed from https://ideas.repec.org/a/spr/cejnor/v23y2015i3p595-606.html
   My bibliography  Save this article

Public service system design with fuzzy parameters of perceived utility

Author

Listed:
  • Jaroslav Janáček

Abstract

Public service systems are designed to satisfy a public demand on some service. The public is represented here by individual users concentrated at dwelling places situated in a served geographical area. The structure of a public service system is determined by a given number of service center locations, which are to be selected from a finite set of possible locations so that utility perceived by the users be maximal. In this paper, we propose an approach to the public service system design, where the utility perceived by an individual user depends on uncertain parameters. The uncertainty is handled using the theory of fuzzy sets in connection with integer programming tools. The suggested way of public service system designing is accompanied by a computational study. Copyright Springer-Verlag Berlin Heidelberg 2015

Suggested Citation

  • Jaroslav Janáček, 2015. "Public service system design with fuzzy parameters of perceived utility," 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 595-606, September.
    • Handle: RePEc:spr:cejnor:v:23:y:2015:i:3:p:595-606
    DOI: 10.1007/s10100-014-0370-7
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10100-014-0370-7
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10100-014-0370-7?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. Drezner, Tammy & Drezner, Zvi, 2007. "The gravity p-median model," European Journal of Operational Research, Elsevier, vol. 179(3), pages 1239-1251, June.
    2. 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.
    3. Jaroslav Janáček & Bohdan Linda & Iva Ritschelová, 2010. "Optimization of Municipalities with Extended Competence Selection," Prague Economic Papers, Prague University of Economics and Business, vol. 2010(1), pages 21-34.
    4. Vladimir Marianov & Daniel Serra, 2004. "Location models in the public sector," Economics Working Papers 755, Department of Economics and Business, Universitat Pompeu Fabra.
    Full references (including those not matched with items on IDEAS)

    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. Jaroslav Janáček & Marek Kvet, 2017. "Semi-fair design of emergency service system with failing centers," 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. 25(3), pages 665-677, September.
    2. 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.
    3. Tao Zhuolin & Zheng Qingjing & Kong Hui, 2018. "A Modified Gravity p-Median Model for Optimizing Facility Locations," Journal of Systems Science and Information, De Gruyter, vol. 6(5), pages 421-434, October.
    4. Soovin Yoon & Laura A. Albert, 2018. "An expected coverage model with a cutoff priority queue," Health Care Management Science, Springer, vol. 21(4), pages 517-533, December.
    5. Carling, Kenneth & Håkansson, Johan, 2012. "A compelling argument for the gravity p-median model," HUI Working Papers 77, HUI Research.
    6. Wajid, Shayesta & Nezamuddin, N., 2023. "Capturing delays in response of emergency services in Delhi," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).
    7. Haase, Knut & Hoppe, Mirko, 2008. "Standortplanung unter Wettbewerb - Teil 1: Grundlagen," Discussion Papers 2/2008, Technische Universität Dresden, "Friedrich List" Faculty of Transport and Traffic Sciences, Institute of Transport and Economics.
    8. Zvi Drezner & Vladimir Marianov & George O. Wesolowsky, 2016. "Maximizing the minimum cover probability by emergency facilities," Annals of Operations Research, Springer, vol. 246(1), pages 349-362, November.
    9. Nilay Noyan, 2010. "Alternate risk measures for emergency medical service system design," Annals of Operations Research, Springer, vol. 181(1), pages 559-589, December.
    10. Westgate, Bradford S. & Woodard, Dawn B. & Matteson, David S. & Henderson, Shane G., 2016. "Large-network travel time distribution estimation for ambulances," European Journal of Operational Research, Elsevier, vol. 252(1), pages 322-333.
    11. G Erdoğan & E Erkut & A Ingolfsson & G Laporte, 2010. "Scheduling ambulance crews for maximum coverage," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(4), pages 543-550, April.
    12. Carling, Kenneth & Han, Mengjie & Håkansson, Johan & Rebreyend, Pascal, 2015. "Testing the gravity p-median model empirically," Operations Research Perspectives, Elsevier, vol. 2(C), pages 124-132.
    13. Noor-E-Alam, Md. & Mah, Andrew & Doucette, John, 2012. "Integer linear programming models for grid-based light post location problem," European Journal of Operational Research, Elsevier, vol. 222(1), pages 17-30.
    14. Berman, Oded & Hajizadeh, Iman & Krass, Dmitry & Rahimi-Vahed, Alireza, 2018. "Reconfiguring a set of coverage-providing facilities under travel time uncertainty," Socio-Economic Planning Sciences, Elsevier, vol. 62(C), pages 1-12.
    15. Jing Yao & Alan T. Murray, 2014. "Locational Effectiveness of Clinics Providing Sexual and Reproductive Health Services to Women in Rural Mozambique," International Regional Science Review, , vol. 37(2), pages 172-193, April.
    16. Bababeik, Mostafa & Khademi, Navid & Chen, Anthony, 2018. "Increasing the resilience level of a vulnerable rail network: The strategy of location and allocation of emergency relief trains," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 119(C), pages 110-128.
    17. Ľudmila Jánošíková & Marek Kvet & Peter Jankovič & Lýdia Gábrišová, 2019. "An optimization and simulation approach to emergency stations relocation," 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. 27(3), pages 737-758, September.
    18. 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.
    19. McCormack, Richard & Coates, Graham, 2015. "A simulation model to enable the optimization of ambulance fleet allocation and base station location for increased patient survival," European Journal of Operational Research, Elsevier, vol. 247(1), pages 294-309.
    20. Zhengna Song & Tinggan Yan & Yunjian Ge, 2018. "Spatial Equilibrium Allocation of Urban Large Public General Hospitals Based on the Welfare Maximization Principle: A Case Study of Nanjing, China," Sustainability, MDPI, vol. 10(9), pages 1-23, August.

    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:cejnor:v:23:y:2015:i:3:p:595-606. 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.