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

Authors: J. Arul Valan; E. Baburaj; P. Parthiban

Addresses: Department of Computer Science and Engineering, National Institute of Technology, Dimapur, Nagaland-797103, India ' Department of Computer Science and Engineering, Marian Engineering College, Trivandrum-695582, India ' Department of Production Engineering, National Institute of Technology, Tiruchirappalli-620015, India

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.

Keywords: influencing factors; relative ranking; interpretive structural modelling; ISM; fuzzy TOPSIS.

DOI: 10.1504/IJMOR.2020.104682

International Journal of Mathematics in Operational Research, 2020 Vol.16 No.1, pp.98 - 117

Received: 05 Apr 2018
Accepted: 14 Sep 2018
Published online: 28 Jan 2020 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article