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Optimization of blood supply chains under different supply scenarios

  • Special: OR in Medicine/Ed. Lee
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Abstract

Blood is a living tissue of unique value to the human body and has special features with short shelf life, unpredictable supply, and stochastic demand. The efficiency of blood management affects the quality of medical services. Scholars pay more attention to demand uncertainty than to supply uncertainty in blood supply chain management, which leads to a lack of research on supply uncertainty in such management. We take supply uncertainty into account and discuss three different uncertainty scenarios: optimistic, average, and pessimistic supply scenarios. Different supply scenarios will affect not only the quantity of orders but also the inventory freshness. To balance the fairness of the old inventory allocation, we designed a hybrid allocation policy of old stocks by order share and batch allocation of other stocks by hospital priority. The simulation results reveal the direct and cross effects of supply uncertainty, life cycle, and old inventory ratio (OIR) policy on the system-wide outdating rate. First, for the effect of supply uncertainty, when it is smaller, the system’s outdate rate grows with the increase of its intensity, but when it is larger, the outdate rate hardly grows and even decreases in intensity. Especially, when the supply uncertainty is larger, the expected supply scenarios have no significant effect on the outdate rate. Second, for the effect of product shelf life, when the shelf life is longer, the OIR policy can significantly reduce the system’s outdate rate in the optimistic or average supply scenarios and has little impact on the rate in the pessimistic supply scenario. Third, for the effect of the OIR policy, when the intensity of supply uncertainty is smaller, the OIR policy leads to a large increase in the system’s outdate rate as supply uncertainty grows. However, when the intensity of supply uncertainty is larger, the range of increase in system outdate rate further increases in the optimistic scenario. In contrast, in the pessimistic scenario, it will decrease. Besides, the OIR policy will have no significant effect on the outdate rate when the supply uncertainty is smaller.

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Acknowledgements

This research is partially supported by National Key R&D Program of China (No. 2020YFB1711900).

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Authors and Affiliations

  1. School of Management and Economics, University of Electronic Science and Technology of China, Chengdu, 611731, China

    Benyong Hu, Longmei Tian, Kangli Zhao & Xu Chen

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  1. Benyong Hu
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Correspondence to Xu Chen.

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Appendices

Appendix A

See Table 

Table 7 Results with Policy 1 under optimistic supply with a range of 5% and \(M = 5\)
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7,

Table 8 Results with Policy 2 under optimistic supply with a range of 5% and \(M = 5\)
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8,

Table 9 Results with Policy 1 under average supply with a range of 5% and \(M = 5\)
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9,

Table 10 Results with Policy 2 under average supply with a range of 5% and \(M = 5\)
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10,

Table 11 Results with Policy 1 under pessimistic supply with a range of 5% and \(M = 5\)
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11,

Table 12 Results with Policy 2 under pessimistic supply with a range of 5% and \(M = 5\)
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12,

Table 13 Results with Policy 1 under optimistic supply with a range of 10% and \(M = 5\)
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13,

Table 14 Results with Policy 2 under optimistic supply with a range of 10% and \(M = 5\)
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14,

Table 15 Results with Policy 1 under average supply with a range of 10% and \(M = 5\)
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15,

Table 16 Results with Policy 2 under average supply with a range of 10% and \(M = 5\)
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16,

Table 17 Results with Policy 1 under pessimistic supply with a range of 10% and \(M = 5\)
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17,

Table 18 Results with Policy 2 under pessimistic supply with a range of 10% and \(M = 5\)
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18,

Table 19 Results with Policy 1 under optimistic supply with a range of 15% and \(M = 5\)
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19,

Table 20 Results with Policy 2 under optimistic supply with a range of 15% and \(M = 5\)
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20,

Table 21 Results with Policy 1 under average supply with a range of 15% and \(M = 5\)
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Table 22 Results with Policy 2 under average supply with a range of 15% and \(M = 5\)
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22,

Table 23 Results with Policy 1 under pessimistic supply with a range of 15% and \(M = 5\)
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Table 24 Results with Policy 2 under pessimistic supply with a range of 15% and \(M = 5\)
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24.

Appendix B

See Table 

Table 25 Results with Policy 1 under optimistic supply with a range of 15% and \(M = 6\)
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25,

Table 26 Results with Policy 2 under optimistic supply with a range of 15% and \(M = 6\)
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26,

Table 27 Results with Policy 1 under average supply with a range of 15% and \(M = 6\)
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27,

Table 28 Results with Policy 2 under average supply with a range of 15% and \(M = 6\)
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28,

Table 29 Results with Policy 1 under pessimistic supply with a range of 15% and \(M = 6\)
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29,

Table 30 Results with Policy 2 under pessimistic supply with a range of 15% and \(M = 6\)
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30,

Table 31 Results with Policy 1 under optimistic supply with a range of 15% and \(M = 7\)
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31,

Table 32 Results with Policy 2 under optimistic supply with a range of 15% and \(M = 7\)
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32,

Table 33 Results with Policy 1 under average supply with a range of 15% and \(M = 7\)
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33,

Table 34 Results with Policy 2 under average supply with a range of 15% and \(M = 7\)
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34,

Table 35 Results with Policy 1 under pessimistic supply with a range of 15% and \(M = 7\)
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35 and

Table 36 Results with Policy 2 under pessimistic supply with a range of 15% and \(M = 7\)
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36.

Appendix C

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Table 37 Results with Policy 1 under reliable supply with \(M = 5\)
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37 and

Table 38 Results with Policy 2 under reliable supply with \(M = 5\)
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38.

Appendix D

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Fig. 13
figure 13

Effect of blood supply uncertainty on supply chain performance

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13 and Table 

Table 39 Results with Policy 1 under optimistic supply with a range of 20% and \(M = 5\)
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39,

Table 40 Results with Policy 2 under optimistic supply with a range of 20% and \(M = 5\)
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40,

Table 41 Results with Policy 1 under average supply with a range of 20% and \(M = 5\)
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41,

Table 42 Results with Policy 2 under average supply with a range of 20% and \(M = 5\)
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42,

Table 43 Results with Policy 1 under pessimistic supply with a range of 20% and \(M = 5\)
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43,

Table 44 Results with Policy 2 under pessimistic supply with a range of 20% and \(M = 5\)
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44.

Appendix E

See Table 

Table 45 Results with Policy 1 under optimistic supply with a range of 15% and \(M = 5\)
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45,

Table 46 Results with Policy 2 under optimistic supply with a range of 15% and \(M = 5\)
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46,

Table 47 Results with Policy 1 under average supply with a range of 15% and \(M = 5\)
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47,

Table 48 Result with Policy 2 under average supply with a range of 15% and \(M = 5\)
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48,

Table 49 Results with Policy 1 under pessimistic supply with a range of 15% and \(M = 5\)
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49 and

Table 50 Results with Policy 2 under pessimistic supply with a range of 15% and \(M = 5\)
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50.

Appendix F

See Fig. 

Fig. 14
figure 14

Effect of blood supply uncertainty on order quantities

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14 and Table 

Table 51 Order quantities with Policy 1 under different supply uncertainty scenarios per month
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51,

Table 52 Order quantities with Policy 2 under different supply uncertainty scenarios per month
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52.

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Hu, B., Tian, L., Zhao, K. et al. Optimization of blood supply chains under different supply scenarios. Ann Oper Res 335, 597–633 (2024). https://doi.org/10.1007/s10479-023-05778-5

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