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Optimizing the Medical Resource Supply Chain During the Covid-19 Pandemic in Baghdad Hospitals using the Fuzzy Inference System (FIS)

Author

Listed:
  • Ansseif A.latif Ansseif

    (Al-Iraqia University, College of Administration and Economics, Iraq. Ph.D. Student at University of Sfax, Tunisia)

  • Abdelaziz Dammak

    (University of Sfax, Laboratory of Modeling and Optimization for Decisional, Industrial and Logistic Systems, Faculty of Economics and Management of Sfax, Tunisia)

Abstract

The importance of using scientific and quantitative methods in addressing contemporary problems, including the (Covid-19) pandemic, as these challenges and problems require everyone, especially those working in educational institutions and researchers, to support international and local efforts to reduce the impact of this pandemic by achieving optimal use of medical resources, for the supply chain of medical resources that includes (therapeutic protocol and medical supplies (; Thus, providing solutions, alternatives and logistical support that would absorb the significant increases in the number of injuries in light of the limited resources in the face of this pandemic. Hence, this research came to contribute to the local and international efforts to address this problem by presenting a package of ideas and solutions for how to achieve the optimal utilization of medical resources. In light of the inaccuracy and discrepancy in the available data by distributing those resources in a quantitative and thoughtful manner to achieve the goal for which it was set, as well as evaluating alternatives on the ground and ways to improve them with an indication of the future prospects for this problem is by applying one of the artificial intelligence techniques called the fuzzy inference system (FIS).

Suggested Citation

  • Ansseif A.latif Ansseif & Abdelaziz Dammak, 2022. "Optimizing the Medical Resource Supply Chain During the Covid-19 Pandemic in Baghdad Hospitals using the Fuzzy Inference System (FIS)," Journal of Mathematics and Statistics Studies, Al-Kindi Center for Research and Development., vol. 3(2), pages 01-17, September.
  • Handle: RePEc:alk:jmss00:v:3:y:2022:i:2:id:4075
    DOI: 10.32996/jmss.2022.3.2.1
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