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Multi-Period Facility Location

In: Location Science

Author

Listed:
  • Stefan Nickel

    (Karlsruhe Institute of Technology (KIT)
    Fraunhofer Institute for Industrial Mathematics (ITWM))

  • Francisco Saldanha Gama

    (Faculdade de Ciências da Universidade de Lisboa)

Abstract

In this chapter, we cover basic aspects related with facility location problems involving time dependent parameters. The emphasis is put on problems defined over a multi-period finite planning horizon. A brief overview of continuous and network problems is presented. Nevertheless, most of the chapter focus on a discrete setting. Basic modeling aspects and solution techniques are discussed. Additionally, some features of practical relevance are considered. The value of the multi-period solution is introduced as a measure for the relevance of considering a multi-period modeling framework instead of a static one. Current challenges and future trends on the topic are discussed.

Suggested Citation

  • Stefan Nickel & Francisco Saldanha Gama, 2015. "Multi-Period Facility Location," Springer Books, in: Gilbert Laporte & Stefan Nickel & Francisco Saldanha da Gama (ed.), Location Science, edition 127, chapter 0, pages 289-310, Springer.
    • Handle: RePEc:spr:sprchp:978-3-319-13111-5_11
    DOI: 10.1007/978-3-319-13111-5_11
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    Citations

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    Cited by:

    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. Tang, Lianhua & Li, Yantong & Bai, Danyu & Liu, Tao & Coelho, Leandro C., 2022. "Bi-objective optimization for a multi-period COVID-19 vaccination planning problem," Omega, Elsevier, vol. 110(C).
    3. Correia, Isabel & Melo, Teresa, 2019. "Dynamic facility location problem with modular capacity adjustments under uncertainty," Technical Reports on Logistics of the Saarland Business School 17, Saarland University of Applied Sciences (htw saar), Saarland Business School.
    4. 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.
    5. Laureano F. Escudero & María Araceli Garín & Celeste Pizarro & Aitziber Unzueta, 2018. "On efficient matheuristic algorithms for multi-period stochastic facility location-assignment problems," Computational Optimization and Applications, Springer, vol. 70(3), pages 865-888, July.
    6. Laureano F. Escudero & Celeste Pizarro Romero, 2017. "On solving a large-scale problem on facility location and customer assignment with interaction costs along a time horizon," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(3), pages 601-622, October.
    7. Vatsa, Amit Kumar & Jayaswal, Sachin, 2021. "Capacitated multi-period maximal covering location problem with server uncertainty," European Journal of Operational Research, Elsevier, vol. 289(3), pages 1107-1126.
    8. Víctor Blanco, 2019. "Ordered p-median problems with neighbourhoods," Computational Optimization and Applications, Springer, vol. 73(2), pages 603-645, June.
    9. Barbati, Maria & Corrente, Salvatore & Greco, Salvatore, 2020. "A general space-time model for combinatorial optimization problems (and not only)," Omega, Elsevier, vol. 96(C).
    10. Jun Zhao & Lixiang Huang, 2019. "Multi-Period Network Design Problem in Regional Hazardous Waste Management Systems," IJERPH, MDPI, vol. 16(11), pages 1-27, June.
    11. Silva, Allyson & Aloise, Daniel & Coelho, Leandro C. & Rocha, Caroline, 2021. "Heuristics for the dynamic facility location problem with modular capacities," European Journal of Operational Research, Elsevier, vol. 290(2), pages 435-452.
    12. Bayraktar, O. Baturhan & Günneç, Dilek & Salman, F. Sibel & Yücel, Eda, 2022. "Relief Aid Provision to En Route Refugees: Multi-Period Mobile Facility Location with Mobile Demand," European Journal of Operational Research, Elsevier, vol. 301(2), pages 708-725.
    13. Vatsa, Amit Kumar & Jayaswal, Sachin, 2016. "A new formulation and Benders decomposition for the multi-period maximal covering facility location problem with server uncertainty," European Journal of Operational Research, Elsevier, vol. 251(2), pages 404-418.
    14. Salman, F. Sibel & Yücel, Eda & Kayı, İlker & Turper-Alışık, Sedef & Coşkun, Abdullah, 2021. "Modeling mobile health service delivery to Syrian migrant farm workers using call record data," Socio-Economic Planning Sciences, Elsevier, vol. 77(C).
    15. Marín, Alfredo & Martínez-Merino, Luisa I. & Rodríguez-Chía, Antonio M. & Saldanha-da-Gama, Francisco, 2018. "Multi-period stochastic covering location problems: Modeling framework and solution approach," European Journal of Operational Research, Elsevier, vol. 268(2), pages 432-449.
    16. Märkle-Huß, Joscha & Feuerriegel, Stefan & Neumann, Dirk, 2020. "Cost minimization of large-scale infrastructure for electricity generation and transmission," Omega, Elsevier, vol. 96(C).
    17. Han, Jialin & Zhang, Jiaxiang & Zeng, Bing & Mao, Mingsong, 2021. "Optimizing dynamic facility location-allocation for agricultural machinery maintenance using Benders decomposition," Omega, Elsevier, vol. 105(C).
    18. Raghavan, S. & Sahin, Mustafa & Salman, F. Sibel, 2019. "The capacitated mobile facility location problem," European Journal of Operational Research, Elsevier, vol. 277(2), pages 507-520.
    19. Dunke, Fabian & Heckmann, Iris & Nickel, Stefan & Saldanha-da-Gama, Francisco, 2018. "Time traps in supply chains: Is optimal still good enough?," European Journal of Operational Research, Elsevier, vol. 264(3), pages 813-829.

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