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An integrated and dynamic optimisation model for the multi-level emergency logistics network in anti-bioterrorism system

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  • Ming Liu
  • Lindu Zhao

Abstract

Demand for emergency resources is usually uncertain and varies quickly in anti-bioterrorism system. Besides, emergency resources which had been allocated to the epidemic areas in the early rescue cycle will affect the demand later. In this article, an integrated and dynamic optimisation model with time-varying demand based on the epidemic diffusion rule is constructed. The heuristic algorithm coupled with the MATLAB mathematical programming solver is adopted to solve the optimisation model. In what follows, the application of the optimisation model as well as a short sensitivity analysis of the key parameters in the time-varying demand forecast model is presented. The results show that both the model and the solution algorithm are useful in practice, and both objectives of inventory level and emergency rescue cost can be controlled effectively. Thus, it can provide some guidelines for decision makers when coping with emergency rescue problem with uncertain demand, and offers an excellent reference when issues pertain to bioterrorism.

Suggested Citation

  • Ming Liu & Lindu Zhao, 2012. "An integrated and dynamic optimisation model for the multi-level emergency logistics network in anti-bioterrorism system," International Journal of Systems Science, Taylor & Francis Journals, vol. 43(8), pages 1464-1478.
    • Handle: RePEc:taf:tsysxx:v:43:y:2012:i:8:p:1464-1478
    DOI: 10.1080/00207721.2010.547629
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    Cited by:

    1. Ubaid Illahi & Mohammad Shafi Mir, 2021. "Maintaining efficient logistics and supply chain management operations during and after coronavirus (COVID-19) pandemic: learning from the past experiences," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(8), pages 11157-11178, August.
    2. 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.
    3. Büyüktahtakın, İ. Esra & des-Bordes, Emmanuel & Kıbış, Eyyüb Y., 2018. "A new epidemics–logistics model: Insights into controlling the Ebola virus disease in West Africa," European Journal of Operational Research, Elsevier, vol. 265(3), pages 1046-1063.
    4. 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.

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