Computational Intelligence Approach to Dynamic Blood Allocation With ABO-Rhesus Factor Compatibility Under Real-World Scenario

Abstract

The supply chain management of blood products specifically deals with the aspect of efficient planning, implementing, and controlling of the in and out flow processes of blood unity in the blood bank system. Therefore, any improvement in the management of these chains would directly influence the manner in which blood and blood products are distributed to all the various sectors requiring such scarce and precious resources. Generally, the management of blood products is difficult due to the four ABO blood groups, which is further complicated by positive/negative rhesus factors. In this paper, a more simplified and robust dynamic mathematical model is presented for the efficient management of the blood bank. The corresponding sets of governing equations from an existing model are extended to cover the rhesus factors and the solution methods of the newly derived equations are subsequently investigated. In addition, a mathematical representation of the decision making process is presented as a function of the blood bank stockpile. Furthermore, in order to demonstrate the robustness of the developed model and to provide managerial insights, a new global hybrid symbiotic organisms search genetic particle swarm optimization algorithm is developed. Several numerical computations are performed using real-world datasets from the Enugu National Blood Transfusion Centre, in Nigeria, which fall within the monthly initial blood volume bounds of 300 over a period of eight years (2010-2018). Finally, the experimental results show that the mathematical model and metaheuristic optimization method proposed in this paper offer a better solution approach for blood allocation in dynamic environments. More so, the impact of some essential control parameters on the results are analysed to help the blood bank managers or decision makers to select accurately the desired parameters for optimal results yield.

Bi-level programming for emergency blood transshipment-allocation considering substitution against public health events

“…In the above model, the objective function (11) is to minimize the total cost including the penalty cost of blood shortage and blood type substitution. The constraint (12) is the expression for the shortage in various hospitals. (13) is the constraint on the transshipment amounts for rescue blood banks.…”

“…In [32], the focus is on the inventory path problem in blood transshipment-allocation, and the result shows that substitution outperforms transshipment at the same cost. In [12], the problem of effective blood bank management is addressed by proposing a dynamic mathematical model that considers the compatible substitution characteristics of different blood types, and a new hybrid heuristic algorithm is proposed, which can provide a better solution for blood transshipment in a dynamic environment. The study being carried out in [47] is on the dynamic decision problem of the blood supply chain, and a model for blood transshipment in an uncertain environment is developed.…”

Importance of Interrelation between ABO Blood Group and Platelet Indices in Young Healthy Adults

“…3,4 Both ABO and Rh groups have pulled in tremendous thought concerning the trend of their relationship with genetic and overpowering ailments. 5 Past assessments of patients with different diseases like tumours, heart morbidities, and parasitic and viral infections exhibited a relationship with these blood groups. 6,7 In different studies, many biological markers of cardiovascular diseases are being identified; for ins-tance, platelet indices like PDW and MPV are suggestive in these studies.…”