IDEAS home Printed from https://ideas.repec.org/a/rom/terumm/v4y2009i1sp87-100.html
   My bibliography  Save this article

Facility Location Models Development To Maximize Total Service Area

Author

Listed:
  • Ahmad Rodzi MAHMUD

    (Universiti Putra Malaysia, Selangor, Malaysia)

  • Vini INDRIASARI

    (Universiti Putra Malaysia, Selangor, Malaysia)

Abstract

This paper present and discuss the new developed model to maximize total service area of a fixed number of facilities. Two greedy algorithms, Greedy Adding (ADD) and Greedy Adding with Substitution (GAS), were applied to solve the optimization problem of the Maximal Service Area Problem (MSAP). The MSAP is a discrete model where a specified number of facilities that achieve the best objective function value of the model are selected out of a finite set of candidate sites. In this study the determination of Fire stations location in Jakarta Selatan, Indonesia, were chosen for simulation. The shape of total service area covered by emergency facilities such as fire stations and ambulances is influenced by the road accessibility. The determination process requires lots of manual intervention in trying to improve the total service area. The two algorithms managed to reach better coverage than the coverage of existing fire stations with the same number of fire stations within the same travel time. The ADD managed to reach the coverage of 82.81% and GAS did 83.20%., while the existing fire stations only reach 73.69%.w. The approach undertaken in conventional facility location models had only defined a facility’s service area simply by a circular coverage. And therefore, it can be concluded that, as such the conventional approach is appropriate for facilities which are not influenced by topographical and road network barriers.

Suggested Citation

  • Ahmad Rodzi MAHMUD & Vini INDRIASARI, 2009. "Facility Location Models Development To Maximize Total Service Area," Theoretical and Empirical Researches in Urban Management, Research Centre in Public Administration and Public Services, Bucharest, Romania, vol. 4(1S), pages 87-100, April.
    • Handle: RePEc:rom:terumm:v:4:y:2009:i:1s:p:87-100
    as

    Download full text from publisher

    File URL: https://um.ase.ro/no1S/8.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Klose, Andreas & Drexl, Andreas, 2005. "Facility location models for distribution system design," European Journal of Operational Research, Elsevier, vol. 162(1), pages 4-29, April.
    2. Jaeggi, D.M. & Parks, G.T. & Kipouros, T. & Clarkson, P.J., 2008. "The development of a multi-objective Tabu Search algorithm for continuous optimisation problems," European Journal of Operational Research, Elsevier, vol. 185(3), pages 1192-1212, March.
    3. CONSTANTINE TOREGAS & CHARLES ReVELLE, 1972. "Optimal Location Under Time Or Distance Constraints," Papers in Regional Science, Wiley Blackwell, vol. 28(1), pages 133-144, January.
    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. Sauvey, Christophe & Melo, Teresa & Correia, Isabel, 2019. "Two-phase heuristics for a multi-period capacitated facility location problem with service-differentiated customers," Technical Reports on Logistics of the Saarland Business School 16, Saarland University of Applied Sciences (htw saar), Saarland Business School.
    2. Zhanwei Tian & Guoqing Zhang, 2021. "Multi-echelon fulfillment warehouse rent and production allocation for online direct selling," Annals of Operations Research, Springer, vol. 304(1), pages 427-451, September.
    3. Ortiz-Astorquiza, Camilo & Contreras, Ivan & Laporte, Gilbert, 2018. "Multi-level facility location problems," European Journal of Operational Research, Elsevier, vol. 267(3), pages 791-805.
    4. Pelegrín, Mercedes & Xu, Liding, 2023. "Continuous covering on networks: Improved mixed integer programming formulations," Omega, Elsevier, vol. 117(C).
    5. Rodolfo Mendoza-Gómez & Roger Z. Ríos-Mercado & Karla B. Valenzuela-Ocaña, 2019. "An Efficient Decision-Making Approach for the Planning of Diagnostic Services in a Segmented Healthcare System," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(05), pages 1631-1665, September.
    6. Delzeit, Ruth & Britz, Wolfgang & Holm-Müller, Karin, 2011. "Modelling regional input markets with numerous processing plants: The case of green maize for biogas production in Germany," Discussion Papers 162892, University of Bonn, Institute for Food and Resource Economics.
    7. Tsekeris, Theodore, 2016. "Interregional trade network analysis for road freight transport in Greece," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 85(C), pages 132-148.
    8. Holzapfel, Andreas & Potoczki, Tobias & Kuhn, Heinrich, 2023. "Designing the breadth and depth of distribution networks in the retail trade," International Journal of Production Economics, Elsevier, vol. 257(C).
    9. Jiwon Baik & Alan T. Murray, 2022. "Locating a facility to simultaneously address access and coverage goals," Papers in Regional Science, Wiley Blackwell, vol. 101(5), pages 1199-1217, October.
    10. Ospina, Juan P. & Duque, Juan C. & Botero-Fernández, Verónica & Montoya, Alejandro, 2022. "The maximal covering bicycle network design problem," Transportation Research Part A: Policy and Practice, Elsevier, vol. 159(C), pages 222-236.
    11. Rentizelas, Athanasios A. & Tatsiopoulos, Ilias P., 2010. "Locating a bioenergy facility using a hybrid optimization method," International Journal of Production Economics, Elsevier, vol. 123(1), pages 196-209, January.
    12. Arana-Jiménez, Manuel & Blanco, Víctor & Fernández, Elena, 2020. "On the fuzzy maximal covering location problem," European Journal of Operational Research, Elsevier, vol. 283(2), pages 692-705.
    13. Correia, Isabel & Melo, Teresa, 2016. "A computational comparison of formulations for a multi-period facility location problem with modular capacity adjustments and flexible demand fulfillment," Technical Reports on Logistics of the Saarland Business School 11, Saarland University of Applied Sciences (htw saar), Saarland Business School.
    14. Pérez-Mesa, Juan Carlos & Galdeano-Gómez, Emilio & Salinas Andújar, Jose A., 2012. "Logistics network and externalities for short sea transport: An analysis of horticultural exports from southeast Spain," Transport Policy, Elsevier, vol. 24(C), pages 188-198.
    15. Boysen, Ole & Schroeder, Carsten, 2006. "Economies of Scale in der Produktion versus Diseconomies im Transport: Zum Strukturwandel im Molkereisektor," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 55(03), pages 1-16.
    16. Emde, Simon & Boysen, Nils, 2012. "Optimally locating in-house logistics areas to facilitate JIT-supply of mixed-model assembly lines," International Journal of Production Economics, Elsevier, vol. 135(1), pages 393-402.
    17. Shen, Xin & Chen, Jin-Ge & Zhu, Xiao-Cheng & Liu, Peng-Yin & Du, Zhao-Hui, 2015. "Multi-objective optimization of wind turbine blades using lifting surface method," Energy, Elsevier, vol. 90(P1), pages 1111-1121.
    18. Sanjay Dominik Jena & Jean-François Cordeau & Bernard Gendron, 2015. "Dynamic Facility Location with Generalized Modular Capacities," Transportation Science, INFORMS, vol. 49(3), pages 484-499, August.
    19. Jesus Gonzalez-Feliu, 2013. "Vehicle Routing in Multi-Echelon Distribution Systems with Cross-Docking: A Systematic Lexical-Metanarrative Analysis," Post-Print halshs-00834573, HAL.
    20. Seyed Hashem Mousavi-Avval & Sami Khanal & Ajay Shah, 2023. "Assessment of Potential Pennycress Availability and Suitable Sites for Sustainable Aviation Fuel Refineries in Ohio," Sustainability, MDPI, vol. 15(13), pages 1-14, July.

    More about this item

    Keywords

    Facility Location; Emergency Facilities; Service Area; Network analysis S.);
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • O21 - Economic Development, Innovation, Technological Change, and Growth - - Development Planning and Policy - - - Planning Models; Planning Policy
    • R30 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - General

    Statistics

    Access and download statistics

    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:rom:terumm:v:4:y:2009:i:1s:p:87-100. 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: Colesca Sofia (email available below). General contact details of provider: https://edirc.repec.org/data/ccasero.html .

    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.