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A simple search heuristic for the MCLP: Application to the location of ambulance bases in a rural region

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  • Adenso-Díaz, B.
  • Rodríguez, F.

Abstract

In the location of ambulance bases for medical assistance, an adequate time of response must be guaranteed for each area in the region covered, incurring the minimum operating costs. Several linear models (such as the maximal covering location problem, MCLP) have been developed for designing these emergency systems which guarantee a certain cover whilst minimising determined costs. The computational difficulty involved in resolving large scale problems occasionally means trying to offer solutions using metaheuristics. This article presents the solution to the problem of locating ambulance bases in the province of Leøn (Spain), using the tabu search metaheuristic, which in its simplest version already offers good results, and which makes it a tool to be kept very much in mind when a rapid solution is needed to such problems.

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  • Adenso-Díaz, B. & Rodríguez, F., 1997. "A simple search heuristic for the MCLP: Application to the location of ambulance bases in a rural region," Omega, Elsevier, vol. 25(2), pages 181-187, April.
    • Handle: RePEc:eee:jomega:v:25:y:1997:i:2:p:181-187
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    References listed on IDEAS

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    Cited by:

    1. Alan T. Murray, 2016. "Maximal Coverage Location Problem," International Regional Science Review, , vol. 39(1), pages 5-27, January.
    2. Bell, John E. & Griffis, Stanley E. & Cunningham III, William A. & Eberlan, Jon A., 2011. "Location optimization of strategic alert sites for homeland defense," Omega, Elsevier, vol. 39(2), pages 151-158, April.
    3. Lei He & Ziang Xie, 2022. "Optimization of Urban Shelter Locations Using Bi-Level Multi-Objective Location-Allocation Model," IJERPH, MDPI, vol. 19(7), pages 1-18, April.
    4. Kusumastuti, Ratih Dyah & Wibowo, Sigit Sulistiyo & Insanita, Rizqiah, 2010. "Hierarchical modeling approach for relief logistics nework Design," MPRA Paper 41089, University Library of Munich, Germany.
    5. Olivera Janković & Stefan Mišković & Zorica Stanimirović & Raca Todosijević, 2017. "Novel formulations and VNS-based heuristics for single and multiple allocation p-hub maximal covering problems," Annals of Operations Research, Springer, vol. 259(1), pages 191-216, December.
    6. Xueping Li & Zhaoxia Zhao & Xiaoyan Zhu & Tami Wyatt, 2011. "Covering models and optimization techniques for emergency response facility location and planning: a review," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 74(3), pages 281-310, December.
    7. Murray, Alan T., 2021. "Contemporary optimization application through geographic information systems," Omega, Elsevier, vol. 99(C).
    8. Matisziw, Timothy C. & Murray, Alan T., 2009. "Siting a facility in continuous space to maximize coverage of a region," Socio-Economic Planning Sciences, Elsevier, vol. 43(2), pages 131-139, June.
    9. Deane, Jason & Agarwal, Anurag, 2012. "Scheduling online advertisements to maximize revenue under variable display frequency," Omega, Elsevier, vol. 40(5), pages 562-570.
    10. Chen, Liang & Chen, Sheng-Jie & Chen, Wei-Kun & Dai, Yu-Hong & Quan, Tao & Chen, Juan, 2023. "Efficient presolving methods for solving maximal covering and partial set covering location problems," European Journal of Operational Research, Elsevier, vol. 311(1), pages 73-87.
    11. James J. Cochran & Martin S. Levy & Jeffrey D. Camm, 2010. "Bayesian coverage optimization models," Journal of Combinatorial Optimization, Springer, vol. 19(2), pages 158-173, February.
    12. Overholts II, Dale L. & Bell, John E. & Arostegui, Marvin A., 2009. "A location analysis approach for military maintenance scheduling with geographically dispersed service areas," Omega, Elsevier, vol. 37(4), pages 838-852, August.

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