IDEAS home Printed from https://ideas.repec.org/a/sae/inrsre/v39y2016i1p77-107.html
   My bibliography  Save this article

The Maximal Cover Location Model with Hedging

Author

Listed:
  • Sam Ratick
  • Jeffrey Osleeb
  • Kangping Si

Abstract

The maximal covering location problem (MCLP) model and the large number of applications and modifications that have emanated from it have been extensively used to site facility networks in a wide variety of applications. In this article, we formulate and apply an extension of MCLP, the Maximal Covering Location Problem with Hedging (MCLPH), to address the problem of siting facilities when the demand for service from those facilities is uncertain. The MCLPH model treats the maximal cover of different potential demand populations in the system as different objectives for the MCLP, with some lexicographic ordering of objectives related to the degree of uncertainty about the sizes and spatial pattern of those demands. We apply the MCLPH model to the problem of designing a medical network of screening facilities for people who may have been exposed to lead contamination in the Dominican Republic (DR). In the DR, there are three suspected sources of lead contamination, waterborne lead from runoff as a result of gold mining activities, airborne lead contamination from the emissions of a battery recycling plant, and airborne lead from the use of leaded gasoline in transportation. The geographical patterns of contamination from these three sources are different and therefore, the populations of the cities and towns in the DR can be expected to be differentially exposed depending upon which is the actual source of the lead. A geographical information system-based hazard analysis is used to provide input data to the MCLPH and to display and evaluate the resulting facility location patterns.

Suggested Citation

  • Sam Ratick & Jeffrey Osleeb & Kangping Si, 2016. "The Maximal Cover Location Model with Hedging," International Regional Science Review, , vol. 39(1), pages 77-107, January.
  • Handle: RePEc:sae:inrsre:v:39:y:2016:i:1:p:77-107
    DOI: 10.1177/0160017615576080
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0160017615576080
    Download Restriction: no

    File URL: https://libkey.io/10.1177/0160017615576080?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
    ---><---

    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. Badri, Masood A. & Mortagy, Amr K. & Alsayed, Colonel Ali, 1998. "A multi-objective model for locating fire stations," European Journal of Operational Research, Elsevier, vol. 110(2), pages 243-260, October.
    3. Charles ReVelle & Kathleen Hogan, 1989. "The Maximum Availability Location Problem," Transportation Science, INFORMS, vol. 23(3), pages 192-200, August.
    4. Current, J. R. & Re Velle, C. S. & Cohon, J. L., 1985. "The maximum covering/shortest path problem: A multiobjective network design and routing formulation," European Journal of Operational Research, Elsevier, vol. 21(2), pages 189-199, August.
    5. Current, John & Min, Hokey & Schilling, David, 1990. "Multiobjective analysis of facility location decisions," European Journal of Operational Research, Elsevier, vol. 49(3), pages 295-307, December.
    6. Kathleen Hogan & Charles ReVelle, 1986. "Concepts and Applications of Backup Coverage," Management Science, INFORMS, vol. 32(11), pages 1434-1444, November.
    7. Richard Church & Charles R. Velle, 1974. "The Maximal Covering Location Problem," Papers in Regional Science, Wiley Blackwell, vol. 32(1), pages 101-118, January.
    8. Kevin Curtin & Karen Hayslett-McCall & Fang Qiu, 2010. "Determining Optimal Police Patrol Areas with Maximal Covering and Backup Covering Location Models," Networks and Spatial Economics, Springer, vol. 10(1), pages 125-145, March.
    9. Kamyoung Kim & Alan T. Murray, 2008. "Enhancing Spatial Representation In Primary And Secondary Coverage Location Modeling," Journal of Regional Science, Wiley Blackwell, vol. 48(4), pages 745-768, October.
    10. Current, John & Ratick, Samuel & ReVelle, Charles, 1998. "Dynamic facility location when the total number of facilities is uncertain: A decision analysis approach," European Journal of Operational Research, Elsevier, vol. 110(3), pages 597-609, November.
    11. 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.
    12. Richard L. Church & Kenneth L. Roberts, 1983. "Generalized Coverage Models And Public Facility Location," Papers in Regional Science, Wiley Blackwell, vol. 53(1), pages 117-135, January.
    13. Samuel Ratick & Brian Meacham & Yuko Aoyama, 2008. "Locating Backup Facilities to Enhance Supply Chain Disaster Resilience," Growth and Change, Wiley Blackwell, vol. 39(4), pages 642-666, December.
    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. Alan T. Murray, 2016. "Maximal Coverage Location Problem," International Regional Science Review, , vol. 39(1), pages 5-27, January.
    2. 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.
    3. Alan Murray, 2010. "Advances in location modeling: GIS linkages and contributions," Journal of Geographical Systems, Springer, vol. 12(3), pages 335-354, September.
    4. 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).
    5. Amin Akbari & Ronald Pelot & H. A. Eiselt, 2018. "A modular capacitated multi-objective model for locating maritime search and rescue vessels," Annals of Operations Research, Springer, vol. 267(1), pages 3-28, August.
    6. Ramon Auad & Rajan Batta, 2017. "Location-coverage models for preventing attacks on interurban transportation networks," Annals of Operations Research, Springer, vol. 258(2), pages 679-717, November.
    7. Stephanie A. Snyder & Robert G. Haight, 2016. "Application of the Maximal Covering Location Problem to Habitat Reserve Site Selection," International Regional Science Review, , vol. 39(1), pages 28-47, January.
    8. 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.
    9. Zhi-Chun Li & Qian Liu, 2020. "Optimal deployment of emergency rescue stations in an urban transportation corridor," Transportation, Springer, vol. 47(1), pages 445-473, February.
    10. Carvalho, A.S. & Captivo, M.E. & Marques, I., 2020. "Integrating the ambulance dispatching and relocation problems to maximize system’s preparedness," European Journal of Operational Research, Elsevier, vol. 283(3), pages 1064-1080.
    11. 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.
    12. O’Hanley, Jesse R. & Scaparra, M. Paola & García, Sergio, 2013. "Probability chains: A general linearization technique for modeling reliability in facility location and related problems," European Journal of Operational Research, Elsevier, vol. 230(1), pages 63-75.
    13. 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.
    14. 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.
    15. Inkyung Sung & Taesik Lee, 2018. "Scenario-based approach for the ambulance location problem with stochastic call arrivals under a dispatching policy," Flexible Services and Manufacturing Journal, Springer, vol. 30(1), pages 153-170, June.
    16. Aytug, Haldun & Saydam, Cem, 2002. "Solving large-scale maximum expected covering location problems by genetic algorithms: A comparative study," European Journal of Operational Research, Elsevier, vol. 141(3), pages 480-494, September.
    17. 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.
    18. A Başar & B Çatay & T Ünlüyurt, 2011. "A multi-period double coverage approach for locating the emergency medical service stations in Istanbul," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(4), pages 627-637, April.
    19. Xu, Jing & Murray, Alan T. & Church, Richard L. & Wei, Ran, 2023. "Service allocation equity in location coverage analytics," European Journal of Operational Research, Elsevier, vol. 305(1), pages 21-37.
    20. KC, Kiran & Corcoran, Jonathan & Chhetri, Prem, 2020. "Measuring the spatial accessibility to fire stations using enhanced floating catchment method," Socio-Economic Planning Sciences, Elsevier, vol. 69(C).

    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:sae:inrsre:v:39:y:2016:i:1:p:77-107. 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: SAGE Publications (email available below). General contact details of provider: .

    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.