The practice of emergency rescue has put forward impending requirements for establishing the national blood strategic reserves (NBSR). An emergency blood support system urgently needs to be constructed in China. However, the characteristics of the blood products and emergency blood support make the location decision-making of NBSR complicated. Hence, a joint LIP is constructed by considering the lead-time, multi-scenarios, multi-stages, multi-blood types, daily stochastic demands, facility capacity constraints and coordinated location with aiming at maximizing timeliness of blood supply under unconventional emergencies. Then, a genetic algorithm is further developed based on the discrete nonlinear mixed integer programming model mentioned above. Finally, two sets of numeral examples is conducted to verify the effectiveness of the model and algorithm. The first set of numeral examples are conducted based on the data which from 31 provincial-level blood centers and provincial-level administrative regions in Chinese Mainland. And 6 numeral examples are given according to different budget values to initially make a location-inventory decision. The second set of numeral examples contains 6 simulation studies under different scales, which are used to test the performance of algorithm proposed in this study. The result shows that the genetic algorithm designed above has a better performance, which can lead to a very small gap (≤ 1.08%) between robust solutions and optimal values of the deterministic model and therobust optimization can reduce the uncertainty risk. In practice, the model constructed in this study can be revised and improved to provide a decision support in solving location-inventory decision problem about relief supplies reserve bases of perishable goods (such as drug, food, etc.) with similar characteristics.
ZHOU Yu-feng, LI Zhi, LIU Si-feng
. Location-inventory Model of National Blood Strategic Reserves based on p-robust Stochastic Optimization Method[J]. Chinese Journal of Management Science, 2018
, 26(10)
: 52
-63
.
DOI: 10.16381/j.cnki.issn1003-207x.2018.10.006
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