IDEAS home Printed from https://ideas.repec.org/a/eee/oprepe/v9y2022ics2214716022000288.html

Reagents and swab tests during the COVID-19 Pandemic: An optimized supply chain management with UAVs

Author

Listed:
  • Colajanni, Gabriella
  • Daniele, Patrizia
  • Sciacca, Daniele

Abstract

In this paper, we develop a supply chain optimization model for the preparation, provision, transportation, and execution of swab tests during COVID-19 pandemic. The proposed approach is based on a multi-tiered network consisting of manufacturing companies of reagents, processing laboratories (where the swab kits are prepared and some swab tests are analyzed), landing stations for UAVs and test centers. As innovations in the supply chain, the sharing of reagents between processing laboratories and the use of UAVs, using 5G technology, are contemplated in the management of the COVID-19 Pandemic. To obtain the optimal solutions of the underlying optimization problem, we provide a variational formulation problem for which results of existence and uniqueness will be provided. Finally, some numerical simulations are examined to validate the effectiveness of our approach.

Suggested Citation

  • Colajanni, Gabriella & Daniele, Patrizia & Sciacca, Daniele, 2022. "Reagents and swab tests during the COVID-19 Pandemic: An optimized supply chain management with UAVs," Operations Research Perspectives, Elsevier, vol. 9(C).
    • Handle: RePEc:eee:oprepe:v:9:y:2022:i:c:s2214716022000288
    DOI: 10.1016/j.orp.2022.100257
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S2214716022000288
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.orp.2022.100257?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Santini, Alberto, 2021. "Optimising the assignment of swabs and reagent for PCR testing during a viral epidemic," Omega, Elsevier, vol. 102(C).
    2. Sawik, Tadeusz, 2022. "Stochastic optimization of supply chain resilience under ripple effect: A COVID-19 pandemic related study," Omega, Elsevier, vol. 109(C).
    3. Caruso, Valeria & Daniele, Patrizia, 2018. "A network model for minimizing the total organ transplant costs," European Journal of Operational Research, Elsevier, vol. 266(2), pages 652-662.
    4. Soheyl Khalilpourazari & Hossein Hashemi Doulabi, 2022. "Designing a hybrid reinforcement learning based algorithm with application in prediction of the COVID-19 pandemic in Quebec," Annals of Operations Research, Springer, vol. 312(2), pages 1261-1305, May.
    5. Nagurney, Anna, 2021. "Optimization of supply chain networks with inclusion of labor: Applications to COVID-19 pandemic disruptions," International Journal of Production Economics, Elsevier, vol. 235(C).
    6. Gabriella Colajanni & Patrizia Daniele & Daniele Sciacca, 2022. "On the Provision of Services With UAVs in Disaster Scenarios: A Two-Stage Stochastic Approach," SN Operations Research Forum, Springer, vol. 3(1), pages 1-30, March.
    7. Patrizia Daniele & Antonino Maugeri & Anna Nagurney, 2017. "Cybersecurity Investments with Nonlinear Budget Constraints: Analysis of the Marginal Expected Utilities," Springer Optimization and Its Applications, in: Nicholas J. Daras & Themistocles M. Rassias (ed.), Operations Research, Engineering, and Cyber Security, pages 117-134, Springer.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ghasemi, Peiman & Ehmke, Jan Fabian & Bicher, Martin, 2025. "Managing equitable contagious disease testing: A mathematical model for resource optimization," Omega, Elsevier, vol. 135(C).

    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. Maleki, Abolfazl & Hemmati, Vahid & Reza Abazari, Seyed & Aghsami, Amir & Rabbani, Masoud, 2024. "Optimal distribution and waste management of Covid-19 vaccines from vaccination centers’ satisfaction perspective – A fuzzy time window-based VRP," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 183(C).
    2. Gilani, Hani & Sahebi, Hadi, 2022. "A data-driven robust optimization model by cutting hyperplanes on vaccine access uncertainty in COVID-19 vaccine supply chain," Omega, Elsevier, vol. 110(C).
    3. Na Wang & Jingze Chen & Hongfeng Wang, 2023. "Resilient Supply Chain Optimization Considering Alternative Supplier Selection and Temporary Distribution Center Location," Mathematics, MDPI, vol. 11(18), pages 1-22, September.
    4. Broekaert, Jan B. & Hafiz, Faizal & Jayaraman, Raja & La Torre, Davide, 2025. "Managing resilience and viability of supranational supply chains under epidemic control scenarios," Omega, Elsevier, vol. 133(C).
    5. Gabriella Colajanni & Patrizia Daniele & Daniele Sciacca, 2022. "On the Provision of Services With UAVs in Disaster Scenarios: A Two-Stage Stochastic Approach," SN Operations Research Forum, Springer, vol. 3(1), pages 1-30, March.
    6. Broekaert, Jan B. & La Torre, Davide & Hafiz, Faizal & Brusset, Xavier, 2025. "The diverging control policy’s hand in supranational supply chain reconfiguration," International Journal of Production Economics, Elsevier, vol. 284(C).
    7. Anna Nagurney & Pritha Dutta, 2019. "Supply chain network competition among blood service organizations: a Generalized Nash Equilibrium framework," Annals of Operations Research, Springer, vol. 275(2), pages 551-586, April.
    8. Ma, Jun & Nault, Barrie R. & Tu, Yiliu (Paul), 2023. "Customer segmentation, pricing, and lead time decisions: A stochastic-user-equilibrium perspective," International Journal of Production Economics, Elsevier, vol. 264(C).
    9. Zhao, Nanyang & Hong, Jiangtao & Lau, Kwok Hung, 2023. "Impact of supply chain digitalization on supply chain resilience and performance: A multi-mediation model," International Journal of Production Economics, Elsevier, vol. 259(C).
    10. Liu, Chong & Tang, Jiaze & Zhang, Zhi-Hai, 2024. "Impacts of capacity redundancy and process flexibility on risk mitigation in e-waste recycling supply chain management," Omega, Elsevier, vol. 128(C).
    11. Hongqin Tang & Jianping Zhu & Nan Li & Weipeng Wu, 2024. "Impact of Enterprise Supply Chain Digitalization on Cost of Debt: A Four-Flows Perspective Analysis Using Explainable Machine Learning Methodology," Sustainability, MDPI, vol. 16(19), pages 1-27, October.
    12. Samia Zaoui & Clovis Foguem & Dieudonné Tchuente & Samuel Fosso-Wamba & Bernard Kamsu-Foguem, 2023. "The Viability of Supply Chains with Interpretable Learning Systems: The Case of COVID-19 Vaccine Deliveries," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 24(4), pages 633-657, December.
    13. Jan B. Broekaert & Davide La Torre & Faizal Hafiz, 2025. "The impact of the psychological effect of infectivity on Nash-balanced control strategies for epidemic networks," Annals of Operations Research, Springer, vol. 351(3), pages 1743-1765, August.
    14. Víctor Hugo de la Cruz Madrigal & Liliana Avelar Sosa & Jose-Manuel Mejía-Muñoz & Jorge Luis García Alcaraz & Emilio Jiménez Macías, 2025. "Dynamical System Modeling for Disruption in Supply Chain and Its Detection Using a Data-Driven Deep Learning-Based Architecture," Logistics, MDPI, vol. 9(2), pages 1-23, April.
    15. 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).
    16. Sagarkumar Hirpara & Monit Vaishnav & Pratik J. Parikh & Nan Kong & Priti Parikh, 2022. "Locating trauma centers considering patient safety," Health Care Management Science, Springer, vol. 25(2), pages 291-310, June.
    17. Ivanov, Dmitry & Dolgui, Alexandre & Sokolov, Boris, 2022. "Cloud supply chain: Integrating Industry 4.0 and digital platforms in the “Supply Chain-as-a-Service”," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 160(C).
    18. Rozhkov, Maxim & Ivanov, Dmitry & Blackhurst, Jennifer & Nair, Anand, 2022. "Adapting supply chain operations in anticipation of and during the COVID-19 pandemic," Omega, Elsevier, vol. 110(C).
    19. Anna Nagurney, 2022. "Supply chain networks, wages, and labor productivity: insights from Lagrange. analysis and computations," Journal of Global Optimization, Springer, vol. 83(3), pages 615-638, July.
    20. Nagurney, Anna & Dutta, Pritha, 2019. "Competition for blood donations," Omega, Elsevier, vol. 85(C), pages 103-114.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    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:eee:oprepe:v:9:y:2022:i:c:s2214716022000288. 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.journals.elsevier.com/operations-research-perspectives .

    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.