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A dynamic logistics model for medical resources allocation in an epidemic control with demand forecast updating

Author

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  • Ming Liu

    (Nanjing University of Science and Technology, Nanjing, P.R. China)

  • Ding Zhang

    (Nanjing University of Science and Technology, Nanjing, P.R. China
    State University of New York, Oswego, USA)

Abstract

This paper presents a dynamic logistics model for medical resources allocation that can be used to control an epidemic diffusion. It couples a forecasting mechanism, constructed for the demand of a medicine in the course of such epidemic diffusion, and a logistics planning system to satisfy the forecasted demand and minimize the total cost. The forecasting mechanism is a time discretized version of the Susceptible-Exposed-Infected-Recovered model that is widely employed in predicting the trajectory of an epidemic diffusion. The logistics planning system is formulated as a mixed 0–1 integer programming problem characterizing the decision making at various levels of hospitals, distribution centers, pharmaceutical plants, and the transportation in between them. The model is built as a closed-loop cycle, comprising forecast phase, planning phase, execution phase, and adjustment phase. The parameters of the forecast mechanism are adjusted in reflection of the real data collected in the execution phase by solving a quadratic programming problem. A numerical example is presented to verify efficiency of the model.

Suggested Citation

  • Ming Liu & Ding Zhang, 2016. "A dynamic logistics model for medical resources allocation in an epidemic control with demand forecast updating," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 67(6), pages 841-852, June.
    • Handle: RePEc:pal:jorsoc:v:67:y:2016:i:6:p:841-852
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    Cited by:

    1. Salarpour, Mojtaba & Nagurney, Anna, 2021. "A multicountry, multicommodity stochastic game theory network model of competition for medical supplies inspired by the Covid-19 pandemic," International Journal of Production Economics, Elsevier, vol. 236(C).
    2. Fabián Silva-Aravena & Irlanda Ceballos-Fuentealba & Eduardo Álvarez-Miranda, 2020. "Inventory Management at a Chilean Hospital Pharmacy: Case Study of a Dynamic Decision-Aid Tool," Mathematics, MDPI, vol. 8(11), pages 1-20, November.
    3. Aarti Singh & Ratri Parida, 2022. "Decision-Making Models for Healthcare Supply Chain Disruptions: Review and Insights for Post-pandemic Era," International Journal of Global Business and Competitiveness, Springer, vol. 17(2), pages 130-141, December.
    4. Xiaoyan Xu & Suresh P. Sethi & Sai‐Ho Chung & Tsan‐Ming Choi, 2023. "Reforming global supply chain management under pandemics: The GREAT‐3Rs framework," Production and Operations Management, Production and Operations Management Society, vol. 32(2), pages 524-546, February.
    5. Biswas, Debajyoti & Alfandari, Laurent, 2022. "Designing an optimal sequence of non‐pharmaceutical interventions for controlling COVID-19," European Journal of Operational Research, Elsevier, vol. 303(3), pages 1372-1391.
    6. Chowdhury, Priyabrata & Paul, Sanjoy Kumar & Kaisar, Shahriar & Moktadir, Md. Abdul, 2021. "COVID-19 pandemic related supply chain studies: A systematic review," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 148(C).
    7. Faghih-Roohi, Shahrzad & Akcay, Alp & Zhang, Yingqian & Shekarian, Ehsan & de Jong, Eelco, 2020. "A group risk assessment approach for the selection of pharmaceutical product shipping lanes," International Journal of Production Economics, Elsevier, vol. 229(C).
    8. Chen, Sihua & Qiu, Han & Wen, Xiang & Wang, Bolin & He, Wei & Shao, Xiuyan, 2024. "Does information disclosure alleviate overcrowding? An empirical study based on large-scale COVID-19 nucleic acid test," Journal of Business Research, Elsevier, vol. 171(C).
    9. Shengjie Long & Dezhi Zhang & Shuangyan Li & Shuanglin Li, 2023. "Two-Stage Multi-Objective Stochastic Model on Patient Transfer and Relief Distribution in Lockdown Area of COVID-19," IJERPH, MDPI, vol. 20(3), pages 1-25, January.
    10. Wang, Qingyi & Liu, Zhuomeng & Jiang, Peng & Luo, Li, 2022. "A stochastic programming model for emergency supplies pre-positioning, transshipment and procurement in a regional healthcare coalition," Socio-Economic Planning Sciences, Elsevier, vol. 82(PB).
    11. Yikai Liu & Ruozheng Wu & Aimin Yang, 2023. "Research on Medical Problems Based on Mathematical Models," Mathematics, MDPI, vol. 11(13), pages 1-26, June.
    12. Liu, Ming & Zhang, Zhe & Zhang, Ding, 2017. "Logistics planning for hospital pharmacy trusteeship under a hybrid of uncertainties," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 101(C), pages 201-215.
    13. 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).
    14. 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.
    15. 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.
    16. Maciel M. Queiroz & Dmitry Ivanov & Alexandre Dolgui & Samuel Fosso Wamba, 2022. "Impacts of epidemic outbreaks on supply chains: mapping a research agenda amid the COVID-19 pandemic through a structured literature review," Annals of Operations Research, Springer, vol. 319(1), pages 1159-1196, December.
    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. Sayarshad, Hamid R., 2023. "Interventions in demand and supply sides for vaccine supply chain: An analysis on monkeypox vaccine," Operations Research Perspectives, Elsevier, vol. 11(C).
    19. Lane, David & Husemann, Elke & Holland, Darren & Khaled, Abdul, 2019. "Understanding foodborne transmission mechanisms for Norovirus: A study for the UK's Food Standards Agency," European Journal of Operational Research, Elsevier, vol. 275(2), pages 721-736.
    20. Kar, Biswajit & Jenamani, Mamata, 2024. "Optimal multimodal multi-echelon vaccine distribution network design for low and medium-income countries with manufacturing infrastructure during healthcare emergencies," International Journal of Production Economics, Elsevier, vol. 273(C).
    21. Hosseini-Motlagh, Seyyed-Mahdi & Samani, Mohammad Reza Ghatreh & Homaei, Shamim, 2023. "Design of control strategies to help prevent the spread of COVID-19 pandemic," European Journal of Operational Research, Elsevier, vol. 304(1), pages 219-238.

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