| dc.description.abstract | Blood supply chains are essential to healthcare systems. A problem is that a
significant portion of the potential blood supply remains untapped, leading to a shortfall in
blood volume collection. The existing blood supply chain is hindered by a scarcity of
permanent facilities for blood collection, compounded by the operational challenges
associated with managing mobile blood collection points. In order to build a blood
collection system across a multi-echalon that includes donor groups, mobile collection
facilities, fixed collection facilities, and a blood bank over a multi-period planning horizon,
a location–allocation model is described in this study. To address the intrinsic epistemic
uncertainty of the model's parameters, a chance-constrained possibilistic programming
technique is used. To solve the model for large-scale issues, a meta-heuristic algorithms is
presented: the imperialist competitive algorithm, moreover, its enhanced variant. In
addition, a number of numerical examples are assessed in order to show the workable
solutions and offer management insights. Finally, a genuine case study of Blood
Transfusion Hematology Hospital in a modern south Vietnamese city is used to illustrate
the applicability of the suggested approach | en_US |
