IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v308y2023i1p422-435.html
   My bibliography  Save this article

On the impact of resource relocation in facing health emergencies

Author

Listed:
  • Barbato, Michele
  • Ceselli, Alberto
  • Premoli, Marco

Abstract

The outbreak of SARS-CoV-2 and the corresponding surge in patients with severe symptoms of COVID-19 put a strain on health systems, requiring specialized material and human resources, often exceeding the locally available ones. Motivated by a real emergency response system employed in Northern Italy, we propose a mathematical programming approach for rebalancing the health resources among a network of hospitals in a large geographical area. It is meant for tactical planning in facing foreseen peaks of patients requiring specialized treatment. Our model has a clean combinatorial structure. At the same time, it considers the handling of patients by a dedicated home healthcare service, and the efficient exploitation of resource sharing. We introduce mathematical programming heuristic based on decomposition methods and column generation to drive very large-scale neighborhood search. We evaluate its embedding in a multi-objective optimization framework. We experiment on real world data of the COVID-19 in Northern Italy during 2020, whose aggregation and post processing is made openly available to the community. Our approach proves to be effective in tackling realistic instances, thus making it a reliable basis for actual decision support tools.

Suggested Citation

  • Barbato, Michele & Ceselli, Alberto & Premoli, Marco, 2023. "On the impact of resource relocation in facing health emergencies," European Journal of Operational Research, Elsevier, vol. 308(1), pages 422-435.
    • Handle: RePEc:eee:ejores:v:308:y:2023:i:1:p:422-435
    DOI: 10.1016/j.ejor.2022.11.024
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221722008803
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ejor.2022.11.024?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Arenas Parra, M. & Bilbao Terol, A. & Perez Gladish, B. & Rodriguez Uria, M. V., 2005. "Solving a multiobjective possibilistic problem through compromise programming," European Journal of Operational Research, Elsevier, vol. 164(3), pages 748-759, August.
    2. 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.
    3. Andersen, Anders Reenberg & Nielsen, Bo Friis & Reinhardt, Line Blander, 2017. "Optimization of hospital ward resources with patient relocation using Markov chain modeling," European Journal of Operational Research, Elsevier, vol. 260(3), pages 1152-1163.
    4. Melo, M.T. & Nickel, S. & Saldanha-da-Gama, F., 2009. "Facility location and supply chain management - A review," European Journal of Operational Research, Elsevier, vol. 196(2), pages 401-412, July.
    5. Jacques Desrosiers & Marco E. Lübbecke, 2005. "A Primer in Column Generation," Springer Books, in: Guy Desaulniers & Jacques Desrosiers & Marius M. Solomon (ed.), Column Generation, chapter 0, pages 1-32, Springer.
    6. Rongbing Huang & Seokjin Kim & Mozart Menezes, 2010. "Facility location for large-scale emergencies," Annals of Operations Research, Springer, vol. 181(1), pages 271-286, December.
    7. 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.
    8. Altay, Nezih & Green III, Walter G., 2006. "OR/MS research in disaster operations management," European Journal of Operational Research, Elsevier, vol. 175(1), pages 475-493, November.
    9. Gian Vincenzo Zuccotti & Simona Bertoli & Andrea Foppiani & Elvira Verduci & Alberto Battezzati, 2020. "COD19 and COD20: An Italian Experience of Active Home Surveillance in COVID-19 Patients," IJERPH, MDPI, vol. 17(18), pages 1-12, September.
    10. Steven Thompson & Manuel Nunez & Robert Garfinkel & Matthew D. Dean, 2009. "OR Practice---Efficient Short-Term Allocation and Reallocation of Patients to Floors of a Hospital During Demand Surges," Operations Research, INFORMS, vol. 57(2), pages 261-273, April.
    11. Corberán, Ángel & Landete, Mercedes & Peiró, Juanjo & Saldanha-da-Gama, Francisco, 2020. "The facility location problem with capacity transfers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 138(C).
    12. Silal, Sheetal Prakash, 2021. "Operational research: A multidisciplinary approach for the management of infectious disease in a global context," European Journal of Operational Research, Elsevier, vol. 291(3), pages 929-934.
    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. Farahani, Reza Zanjirani & Fallah, Samira & Ruiz, Rubén & Hosseini, Sara & Asgari, Nasrin, 2019. "OR models in urban service facility location: A critical review of applications and future developments," European Journal of Operational Research, Elsevier, vol. 276(1), pages 1-27.
    2. Saldanha-da-Gama, Francisco, 2022. "Facility Location in Logistics and Transportation: An enduring relationship," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 166(C).
    3. Dönmez, Zehranaz & Kara, Bahar Y. & Karsu, Özlem & Saldanha-da-Gama, Francisco, 2021. "Humanitarian facility location under uncertainty: Critical review and future prospects," Omega, Elsevier, vol. 102(C).
    4. 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.
    5. 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.
    6. Jesus Gonzalez-Feliu, 2013. "Vehicle Routing in Multi-Echelon Distribution Systems with Cross-Docking: A Systematic Lexical-Metanarrative Analysis," Post-Print halshs-00834573, HAL.
    7. Laijun Zhao & Huiyong Li & Yan Sun & Rongbing Huang & Qingmi Hu & Jiajia Wang & Fei Gao, 2017. "Planning Emergency Shelters for Urban Disaster Resilience: An Integrated Location-Allocation Modeling Approach," Sustainability, MDPI, vol. 9(11), pages 1-20, November.
    8. Olivares-Benitez, Elias & Ríos-Mercado, Roger Z. & González-Velarde, José Luis, 2013. "A metaheuristic algorithm to solve the selection of transportation channels in supply chain design," International Journal of Production Economics, Elsevier, vol. 145(1), pages 161-172.
    9. Bhuvnesh Sharma & M. Ramkumar & Nachiappan Subramanian & Bharat Malhotra, 2019. "Dynamic temporary blood facility location-allocation during and post-disaster periods," Annals of Operations Research, Springer, vol. 283(1), pages 705-736, December.
    10. Ashu Kedia & Diana Kusumastuti & Alan Nicholson, 2019. "Establishing Collection and Delivery Points to Encourage the Use of Active Transport: A Case Study in New Zealand Using a Consumer-Centric Approach," Sustainability, MDPI, vol. 11(22), pages 1-23, November.
    11. Ansari, Sina & Başdere, Mehmet & Li, Xiaopeng & Ouyang, Yanfeng & Smilowitz, Karen, 2018. "Advancements in continuous approximation models for logistics and transportation systems: 1996–2016," Transportation Research Part B: Methodological, Elsevier, vol. 107(C), pages 229-252.
    12. Rodríguez-Espíndola, Oscar & Ahmadi, Hossein & Gastélum-Chavira, Diego & Ahumada-Valenzuela, Omar & Chowdhury, Soumyadeb & Dey, Prasanta Kumar & Albores, Pavel, 2023. "Humanitarian logistics optimization models: An investigation of decision-maker involvement and directions to promote implementation," Socio-Economic Planning Sciences, Elsevier, vol. 89(C).
    13. Schuster Puga, Matías & Minner, Stefan & Tancrez, Jean-Sébastien, 2019. "Two-stage supply chain design with safety stock placement decisions," International Journal of Production Economics, Elsevier, vol. 209(C), pages 183-193.
    14. Güden, Hüseyin & Süral, Haldun, 2014. "Locating mobile facilities in railway construction management," Omega, Elsevier, vol. 45(C), pages 71-79.
    15. Kidd, Martin P. & Darvish, Maryam & Coelho, Leandro C. & Gendron, Bernard, 2024. "A relax-and-restrict matheuristic for supply chain network design with facility location and customer due date flexibility," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 182(C).
    16. Mittal, Neha & Boile, Maria & Baveja, Alok & Theofanis, Sotiris, 2013. "Determining optimal inland-empty-container depot locations under stochastic demand," Research in Transportation Economics, Elsevier, vol. 42(1), pages 50-60.
    17. Mohsen Moghaddam & Shimon Y. Nof & Ehud Menipaz, 2016. "Design and administration of collaborative networked headquarters," International Journal of Production Research, Taylor & Francis Journals, vol. 54(23), pages 7074-7090, December.
    18. Luca Bertazzi & Francesca Maggioni, 2015. "Solution Approaches for the Stochastic Capacitated Traveling Salesmen Location Problem with Recourse," Journal of Optimization Theory and Applications, Springer, vol. 166(1), pages 321-342, July.
    19. Gross, Wendelin & Butz, Christian, 2014. "Design of Sustainable Transportation Networks," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Kersten, Wolfgang & Blecker, Thorsten & Ringle, Christian M. (ed.), Next Generation Supply Chains: Trends and Opportunities. Proceedings of the Hamburg International Conference of Logistics (HICL), Vol. 18, volume 18, pages 137-160, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    20. Christophe Duhamel & Andréa Cynthia Santos & Daniel Brasil & Eric Châtelet & Babiga Birregah, 2016. "Connecting a population dynamic model with a multi-period location-allocation problem for post-disaster relief operations," Annals of Operations Research, Springer, vol. 247(2), pages 693-713, December.

    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:eee:ejores:v:308:y:2023:i:1:p:422-435. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    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.