血液為一種具有固定性壽命之易腐性商品，會隨著保存時間的減短而降低品質，醫院必須提高血液的存貨控制的重要性，血液存貨過多或過少時，可能會產生不必要的社會資源浪費及增加病患治療的風險。而在醫療臨床的需求中，血液為一項必不可缺的重要資源，其中，以血小板的壽命最短，自捐贈後僅約有五天之壽命，更顯其存貨管理的重要性，因此本研究將以血小板為主要研究對象。
本研究提出一個結合類神經網路與模擬最佳化的方法，由於血液的需求及供給皆是不確定性的，會隨著時間或事件的發生而波動，形成一時間序列，長短期記憶網路可針對過去資料判斷其重要性而採取記憶或忘記，主要適合處理或預測與時間序列相關之問題，因此，本研究將利用長短期記憶網路預測未來血小板的供應量，接著以模擬最佳化的方法求解該期最佳存貨策略參數，最後利用類神經網路模型，學習預測供應量與最佳存貨策略參數之間的關係，預測該期之最佳存貨策略參數，提供血庫管理人員控制血液捐贈量，另外，本研究之模型以星期為單位，預測在該單位內每日的存貨策略參數，並利用缺貨數量、過期數量、總存貨成本及供應的血小板平均剩餘壽命作為衡量指標。
透過實際捐血中心血小板資料進行模式驗證，利用不同的存貨策略對血小板的存貨進行管理，相較於捐血中心目前所採行的管理方法，本研究所提出的方法造成的缺貨及過期情形較佳，並發現：當缺貨數量較多時，供應的血小板平均剩餘壽命較高，當過期數量較多時，平均剩餘壽命較低，在存貨策略方面，相較於目標存貨水準策略，(s, Q)存貨策略利用安全存量控制庫存，使得過期數量較低，但亦使得缺貨數量較多。
本研究提出之方法提供血庫管理人員能夠明確控制血小板的存貨，依據管理需求採取不同的存貨策略，並將過期處理、缺貨及存貨持有成本降到最低，甚至能夠將此方法應用至其他血品之存貨管理。

Blood is not only an indispensable medical resource in the hospital but also a perish product with a limited shelf life which will reduce the quality as the storage time shortens. It may cause unnecessary waste of social resources or increase the risk of patient treatment. Across all blood types, the shelf life of platelets is only five days after donation, which shows the importance of inventory management. In the past, most research used the Taguchi method to solve the optimal parameters and considered only one inventory policy. We propose a model combining the neural networks and simulation optimization, not only taking the trend of platelet demand into consideration but also discussing multiple inventory policies. Firstly, we use Long Short-Term Memory (LSTM) to predict the demand of the hospitals and use simulation optimization to find the optimal parameters. Secondly, considering the predicting demand of hospitals and the optimal parameters simultaneously, we use LSTM to predict the corresponding parameters. This model was tested in six scenarios, and we used the number of shortages, expiration, total inventory cost and average remaining life to evaluate the performance. Finally, a numerical example is presented to demonstrate this model accompanied by sensitivity analysis. The results in all scenarios performed better than the baseline, and the best performance was when there is was high donation limit. The number of shortages is lower when using the order-up to policy and periodic inventory system. The amount of expired blood is lower when using the (s, Q) policy. Some managerial insights are obtained from the results, which will assist the blood center in improving its inventory management.

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