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Data analytics for relative ranking of factors to optimise blood bank supply chain

Author

Listed:
  • J. Arul Valan
  • E. Baburaj
  • P. Parthiban

Abstract

Healthcare systems are supported by blood service operations. Restricted usage limit of 21 days and stochastic nature of demand against the supply are the challenges in the field and results in complex situations. The paper focuses on the model mentioned for which a regionalised blood banking system is considered. Typically, it consists of hospitals, regional blood banks, in addition to central blood banks. The 20 factors that influence is weighed and raked using multiple criterion decision making (MCDM) methods. Interpretive structural modelling (ISM) gives the influence of a factor on another and determines weights. Fuzzy-TOPSIS is used to quantify the qualitative values systematically and rank the alternatives. The relative ranking enables to identify best alternative. The procedure for a single central blood bank executed may be extended to similar central blood banks. Supply chain optimisation of perishable products is possible with the framework proposed, with suitable modifications.

Suggested Citation

  • J. Arul Valan & E. Baburaj & P. Parthiban, 2020. "Data analytics for relative ranking of factors to optimise blood bank supply chain," International Journal of Mathematics in Operational Research, Inderscience Enterprises Ltd, vol. 16(1), pages 98-117.
    • Handle: RePEc:ids:ijmore:v:16:y:2020:i:1:p:98-117
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