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Open-source approaches for location cover models: capabilities and efficiency

Author

Listed:
  • Huanfa Chen

    (University College London)

  • Alan T. Murray

    (University of California at Santa Barbara)

  • Rui Jiang

    (University College London)

Abstract

Location cover models are aimed at siting facilities so as to provide service to demand efficiently. These models are crucial in the management, planning and decision-making of service systems in public and private sectors. As a result, location cover models have been incorporated in a range of GIS tools, either closed or open source. Among them, open-source tools are advantageous due to transparency and reproducibility. Nonetheless, the capabilities and limitations of location cover tools remain largely unknown, necessitating further investigation and assessment. To this end, this paper provides an overview of the open-source tools that are capable of structuring and solving location cover models. Case studies are provided to demonstrate access of location models through different open-source tools as well as exploring solution quality, scalability, computing performance and reproducibility. Directions for improving location cover models accessible through open-source tools are summarized based on this review.

Suggested Citation

  • Huanfa Chen & Alan T. Murray & Rui Jiang, 2021. "Open-source approaches for location cover models: capabilities and efficiency," Journal of Geographical Systems, Springer, vol. 23(3), pages 361-380, July.
    • Handle: RePEc:kap:jgeosy:v:23:y:2021:i:3:d:10.1007_s10109-021-00350-w
    DOI: 10.1007/s10109-021-00350-w
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    References listed on IDEAS

    as
    1. Constantine Toregas & Ralph Swain & Charles ReVelle & Lawrence Bergman, 1971. "The Location of Emergency Service Facilities," Operations Research, INFORMS, vol. 19(6), pages 1363-1373, October.
    2. Ron Buliung & Tarmo Remmel, 2008. "Open source, spatial analysis, and activity-travel behaviour research: capabilities of the aspace package," Journal of Geographical Systems, Springer, vol. 10(2), pages 191-216, June.
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    4. Manfred M. Fischer & Arthur Getis (ed.), 2010. "Handbook of Applied Spatial Analysis," Springer Books, Springer, number 978-3-642-03647-7, July.
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    6. Daoqin Tong & Alan T. Murray, 2009. "Maximising coverage of spatial demand for service," Papers in Regional Science, Wiley Blackwell, vol. 88(1), pages 85-97, March.
    7. Richard L. Church & Alan Murray, 2018. "Location Covering Models," Advances in Spatial Science, Springer, number 978-3-319-99846-6, February.
    8. Alan Murray, 2010. "Advances in location modeling: GIS linkages and contributions," Journal of Geographical Systems, Springer, vol. 12(3), pages 335-354, September.
    9. Murray, Alan T. & Wei, Ran, 2013. "A computational approach for eliminating error in the solution of the location set covering problem," European Journal of Operational Research, Elsevier, vol. 224(1), pages 52-64.
    10. Richard Church & Charles R. Velle, 1974. "The Maximal Covering Location Problem," Papers in Regional Science, Wiley Blackwell, vol. 32(1), pages 101-118, January.
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    Cited by:

    1. Alan T. Murray & Antonio Ortiz & Seonga Cho, 2022. "Enhancing strategic defensive positioning and performance in the outfield," Journal of Geographical Systems, Springer, vol. 24(2), pages 223-240, April.

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    More about this item

    Keywords

    Spatial optimisation; Location cover model; Open source; GIS;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software
    • Q15 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Land Ownership and Tenure; Land Reform; Land Use; Irrigation; Agriculture and Environment

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