During COVID-19, blood demand exceeded pre-pandemic levels due to reduced donations, causing shortages. Given the severe shortage, it's crucial to optimise blood use, prevent shortages, minimise wastage, and reduc...
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During COVID-19, blood demand exceeded pre-pandemic levels due to reduced donations, causing shortages. Given the severe shortage, it's crucial to optimise blood use, prevent shortages, minimise wastage, and reduce unnecessary transfusions in all hospitalised patients. Designing a reliable blood supply chain network (BSCN) is an effective solution, especially for COVID-19 patients. This strategic decision significantly impacts emergency management performance. An efficient and reliable blood supply chain requires the consideration of multiple factors, including scarceness and perishability of blood, simultaneously. However, existing studies have not addressed all relevant factors in an integrated blood supply chain, and this paper aims to bridge this gap. Furthermore, an efficient Benders Decomposition based heuristic approach is proposed to solve the model. The solution approach has been compared with a set of commonly used meta-heuristicalgorithms, including the red deer algorithm (RDA), tree growth algorithm (TGA), and genetic algorithm (GA). The outcomes illustrate that the proposed heuristic approach can solve small and large-size problems in significantly less CPU time than the other proposed solution approaches. For large-size problems, it can reduce the average CPU time by about 80% compared to TGA, about 80% compared to GA, and about 83% compared to RDA. A real case study has been implemented to validate the proposed mathematical model and solution method. The sensitivity analysis has been conducted to validate the significance of the model's parameters;consequently, several managerial insights have been derived.
The COVID-19 pandemic has highlighted the stability of the blood supply chain in case of interruption and other emergencies. Blood is a precious and perishable substance, and any disruption in its supply can cause ser...
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The COVID-19 pandemic has highlighted the stability of the blood supply chain in case of interruption and other emergencies. Blood is a precious and perishable substance, and any disruption in its supply can cause serious consequences. Current research on the blood supply chain mostly focuses on a multi-objective perspective, and rarely involves both multi-objective and multi-period methods simultaneously. Therefore, we develop a multi-period multi-objective closed-loop blood supply chain model that considers disruptions and uncertainties of demand and recovery, aiming at achieving a balance among various objectives, and coordination of various periods. Fuzzy chance-constraint, meta-heuristic approaches and exact solution (CLPEX) are adopted to mitigate the impact of uncertainties and calculate the optimal solution of a calculating case. The calculation outcomes indicate that: With regard to economic costs and social benefit, the multi-period system is better than the single-period system;the comprehensive performance of the multi-target system is better than that of the single-target system;and the multi-period multi-objective system is more in line with the real situation. Meanwhile, the mitigation strategies, such as maintaining emergency inventory and implementing lateral transshipment, can significantly enhance the performance of the system in disruptions. This paper mainly contributes the follows: Firstly, it provides a reference for configuration and optimisation of a cross-region closed-loop supply chain under disruptions and uncertainties. Secondly, the comprehensive trade-off of multi-objective and multi-period in this paper is especially suitable for perishable production with short cycles, large fluctuations of supply and demand.
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