IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v328y2023i1d10.1007_s10479-022-04713-4.html
   My bibliography  Save this article

Designing an integrated responsive-green-cold vaccine supply chain network using Internet-of-Things: artificial intelligence-based solutions

Author

Listed:
  • Fariba Goodarzian

    (Machine Intelligence Research Labs (MIR Labs), Scientific Network for Innovation and Research Excellence
    University of Seville)

  • Ali Navaei

    (University of Tehran)

  • Behdad Ehsani

    (HEC Montréal)

  • Peiman Ghasemi

    (German University of Technology in Oman (GUtech))

  • Jesús Muñuzuri

    (University of Seville)

Abstract

In this paper, a new responsive-green-cold vaccine supply chain network during the COVID-19 pandemic is developed for the first time. According to the proposed network, a new multi-objective, multi-period, multi-echelon mathematical model for the distribution-allocation-location problem is designed. Another important novelty in this paper is that it considers an Internet-of-Things application in the COVID-19 condition in the suggested model to enhance the accuracy, speed, and justice of vaccine injection with existing priorities. Waste management, environmental effects, coverage demand, and delivery time of COVID-19 vaccine simultaneously are therefore considered for the first time. The LP-metric method and meta-heuristic algorithms called Gray Wolf Optimization (GWO), and Variable Neighborhood Search (VNS) algorithms are then used to solve the developed model. The other significant contribution, based on two presented meta-heuristic algorithms, is a new heuristic method called modified GWO (MGWO), and is developed for the first time to solve the model. Therefore, a set of test problems in different sizes is provided. Hence, to evaluate the proposed algorithms, assessment metrics including (1) percentage of domination, (2) the number of Pareto solutions, (3) data envelopment analysis, and (4) diversification metrics and the performance of the convergence are considered. Moreover, the Taguchi method is used to tune the algorithm’s parameters. Accordingly, to illustrate the efficiency of the model developed, a real case study in Iran is suggested. Finally, the results of this research show MGO offers higher quality and better performance than other proposed algorithms based on assessment metrics, computational time, and convergence.

Suggested Citation

  • Fariba Goodarzian & Ali Navaei & Behdad Ehsani & Peiman Ghasemi & Jesús Muñuzuri, 2023. "Designing an integrated responsive-green-cold vaccine supply chain network using Internet-of-Things: artificial intelligence-based solutions," Annals of Operations Research, Springer, vol. 328(1), pages 531-575, September.
    • Handle: RePEc:spr:annopr:v:328:y:2023:i:1:d:10.1007_s10479-022-04713-4
    DOI: 10.1007/s10479-022-04713-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10479-022-04713-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10479-022-04713-4?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. Lejeune, M.A., 2006. "A variable neighborhood decomposition search method for supply chain management planning problems," European Journal of Operational Research, Elsevier, vol. 175(2), pages 959-976, December.
    2. Shamsi G., N. & Ali Torabi, S. & Shakouri G., H., 2018. "An option contract for vaccine procurement using the SIR epidemic model," European Journal of Operational Research, Elsevier, vol. 267(3), pages 1122-1140.
    3. Klemeš, Jiří Jaromír & Fan, Yee Van & Tan, Raymond R. & Jiang, Peng, 2020. "Minimising the present and future plastic waste, energy and environmental footprints related to COVID-19," Renewable and Sustainable Energy Reviews, Elsevier, vol. 127(C).
    4. Yang, Yuwen & Bidkhori, Hoda & Rajgopal, Jayant, 2021. "Optimizing vaccine distribution networks in low and middle-income countries," Omega, Elsevier, vol. 99(C).
    5. Hao Yu & Xu Sun & Wei Deng Solvang & Xu Zhao, 2020. "Reverse Logistics Network Design for Effective Management of Medical Waste in Epidemic Outbreaks: Insights from the Coronavirus Disease 2019 (COVID-19) Outbreak in Wuhan (China)," IJERPH, MDPI, vol. 17(5), pages 1-25, March.
    6. 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).
    7. Yu, Anyu & Shi, Yu & You, Jianxin & Zhu, Joe, 2021. "Innovation performance evaluation for high-tech companies using a dynamic network data envelopment analysis approach," European Journal of Operational Research, Elsevier, vol. 292(1), pages 199-212.
    8. Sube Singh & Ramesh Kumar & Rohit Panchal & Manoj Kumar Tiwari, 2021. "Impact of COVID-19 on logistics systems and disruptions in food supply chain," International Journal of Production Research, Taylor & Francis Journals, vol. 59(7), pages 1993-2008, April.
    9. Mohamed Ben-Daya & Elkafi Hassini & Zied Bahroun, 2019. "Internet of things and supply chain management: a literature review," International Journal of Production Research, Taylor & Francis Journals, vol. 57(15-16), pages 4719-4742, August.
    10. Duijzer, Lotty Evertje & van Jaarsveld, Willem & Dekker, Rommert, 2018. "Literature review: The vaccine supply chain," European Journal of Operational Research, Elsevier, vol. 268(1), pages 174-192.
    11. Lin, Qi & Zhao, Qiuhong & Lev, Benjamin, 2020. "Cold chain transportation decision in the vaccine supply chain," European Journal of Operational Research, Elsevier, vol. 283(1), pages 182-195.
    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. Choudhury, Nishat Alam & Ramkumar, M. & Schoenherr, Tobias & Singh, Shalabh, 2023. "The role of operations and supply chain management during epidemics and pandemics: Potential and future research opportunities," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 175(C).
    2. Eugenia Ama Andoh & Hao Yu, 2023. "A two-stage decision-support approach for improving sustainable last-mile cold chain logistics operations of COVID-19 vaccines," Annals of Operations Research, Springer, vol. 328(1), pages 75-105, September.
    3. Lin, Qi & Zhao, Qiuhong & Lev, Benjamin, 2022. "Influenza vaccine supply chain coordination under uncertain supply and demand," European Journal of Operational Research, Elsevier, vol. 297(3), pages 930-948.
    4. 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).
    5. Xie, Lei & Hou, Pengwen & Han, Hongshuai, 2021. "Implications of government subsidy on the vaccine product R&D when the buyer is risk averse," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 146(C).
    6. Min Su & Qiang Wang & Rongrong Li, 2021. "How to Dispose of Medical Waste Caused by COVID-19? A Case Study of China," IJERPH, MDPI, vol. 18(22), pages 1-18, November.
    7. Piotr Nowakowski & Sandra Kuśnierz & Patrycja Sosna & Jakub Mauer & Dawid Maj, 2020. "Disposal of Personal Protective Equipment during the COVID-19 Pandemic Is a Challenge for Waste Collection Companies and Society: A Case Study in Poland," Resources, MDPI, vol. 9(10), pages 1-11, September.
    8. Muhammad Umar Farooq & Amjad Hussain & Tariq Masood & Muhammad Salman Habib, 2021. "Supply Chain Operations Management in Pandemics: A State-of-the-Art Review Inspired by COVID-19," Sustainability, MDPI, vol. 13(5), pages 1-33, February.
    9. Esmizadeh, Yalda & Bashiri, Mahdi & Jahani, Hamed & Almada-Lobo, Bernardo, 2021. "Cold chain management in hierarchical operational hub networks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 147(C).
    10. Yadav, Amit Kumar & Shweta, & Kumar, Dinesh, 2023. "Blockchain technology and vaccine supply chain: Exploration and analysis of the adoption barriers in the Indian context," International Journal of Production Economics, Elsevier, vol. 255(C).
    11. Muckstadt, John A. & Klein, Michael G. & Jackson, Peter L. & Gougelet, Robert M. & Hupert, Nathaniel, 2023. "Efficient and effective large-scale vaccine distribution," International Journal of Production Economics, Elsevier, vol. 262(C).
    12. Florin-Constantin Mihai, 2020. "Assessment of COVID-19 Waste Flows During the Emergency State in Romania and Related Public Health and Environmental Concerns," IJERPH, MDPI, vol. 17(15), pages 1-18, July.
    13. Hu, Hui & Xu, Jiajun & Liu, Mengqi & Lim, Ming K., 2023. "Vaccine supply chain management: An intelligent system utilizing blockchain, IoT and machine learning," Journal of Business Research, Elsevier, vol. 156(C).
    14. Agnieszka Szmelter-Jarosz & Javid Ghahremani-Nahr & Hamed Nozari, 2021. "A Neutrosophic Fuzzy Optimisation Model for Optimal Sustainable Closed-Loop Supply Chain Network during COVID-19," JRFM, MDPI, vol. 14(11), pages 1-22, November.
    15. Fadaki, Masih & Abareshi, Ahmad & Far, Shaghayegh Maleki & Lee, Paul Tae-Woo, 2022. "Multi-period vaccine allocation model in a pandemic: A case study of COVID-19 in Australia," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 161(C).
    16. Yin Ting Chu & Jianzhao Zhou & Yuan Wang & Yue Liu & Jingzheng Ren, 2023. "Current State, Development and Future Directions of Medical Waste Valorization," Energies, MDPI, vol. 16(3), pages 1-28, January.
    17. Manupati, Vijaya Kumar & Schoenherr, Tobias & Subramanian, Nachiappan & Ramkumar, M. & Soni, Bhanushree & Panigrahi, Suraj, 2021. "A multi-echelon dynamic cold chain for managing vaccine distribution," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 156(C).
    18. Vahdani, Behnam & Mohammadi, Mehrdad & Thevenin, Simon & Gendreau, Michel & Dolgui, Alexandre & Meyer, Patrick, 2023. "Fair-split distribution of multi-dose vaccines with prioritized age groups and dynamic demand: The case study of COVID-19," European Journal of Operational Research, Elsevier, vol. 310(3), pages 1249-1272.
    19. Tushar, Saifur Rahman & Alam, Md. Fahim Bin & Bari, A.B.M. Mainul & Karmaker, Chitra Lekha, 2023. "Assessing the challenges to medical waste management during the COVID-19 pandemic: Implications for the environmental sustainability in the emerging economies," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).
    20. Klemeš, Jiří Jaromír & Jiang, Peng & Fan, Yee Van & Bokhari, Awais & Wang, Xue-Chao, 2021. "COVID-19 pandemics Stage II – Energy and environmental impacts of vaccination," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).

    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:spr:annopr:v:328:y:2023:i:1:d:10.1007_s10479-022-04713-4. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.