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  1. توسعه رویکردی کاربردی برای توسعه برنامه‌ریزی زنجیره تامین واکسن و دارو در شرایط اپیدمی
توسعه رویکردی کاربردی برای توسعه برنامه‌ریزی زنجیره تامین واکسن و دارو در شرایط اپیدمی
750 viewed

توسعه رویکردی کاربردی برای توسعه برنامه‌ریزی زنجیره تامین واکسن و دارو در شرایط اپیدمی

کوچک کاشانی، فرید Kochak Kashani, Farid

Developing Vaccine and Pharmaceuticals Supply Chain Planning in Epidemic Crisis: An Applied Approach

Kochak Kashani, Farid | 2022

750 Viewed
  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 54780 (01)
  4. University: Sharif University of Technology
  5. Department: Industrial Engineering
  6. Advisor(s): Haji, Alireza; Kayvanfar, Vahid
  7. Abstract:
  8. As an abrupt epidemic takes place, most healthcare systems are shocked by the surge in the number of susceptible patients’ demands, and decision-makers mostly rely on their frame of reference to deal with the emergency situation as soon as possible. This paper aims to provide a mathematical model as a reliable support for pharmaceutical supply chain planning for the case of the COVID-19 epidemic. Additionally, it aims to integrate cold and non-cold chains is to take into account various pharmaceuticals and vaccines. To propose a model for planning the pharmaceutical supply chains, a mixed-integer linear programming (MILP) model is used for a four-echelon supply chain design. This model aims to minimize the costs involved in pharmaceuticals supply chain with maintaining an acceptable service level. Also, this paper considers uncertainty as an intrinsic part of the problem and through using a stochastic programming method, called wait-and-see, it models the uncertain problem. In order to take into account numerous pharmaceuticals and vaccines with their individual characteristics, such as priority, temperature, and volume, the K-means clustering method was used. A case of Tehran hospitals with real data has been used to show the model’s capabilities. The proposed MILP model has proven to be efficient for providing a practical intuition for decision-makers. The clustering technique reduced the size of the problem and the time required to solve the model considerably. Sensitivity analysis drawn from the study results granted valuable implications for adjusting the model during different epidemic stages
  9. Keywords:
  10. Health Care System ; Supply Chain Management (SCM) ; Mathematical Modeling ; Stochastic Programming ; K-means Clustering ; Hospital Supply Chain ; Vaccine Supply Chain

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