本研究考慮訂貨型製造業的產能配給問題。此隨機問題環境為在工廠的產能有限，且需求訂單來到為普瓦松過程(Poisson process)的情況下，決策業者應如何決策是否接受該訂單以最大化利潤。在本問題中，訂單隨機地來到，且每張訂單有不同的最早可加工時間、交期、處理時間、及利潤。在實際情況中，當有訂單來到時，管理者必須立刻決定是否要接受該訂單的需求。若是接受需求，工廠的剩餘產能將會減少，並增加此訂單所帶來的收益。若是拒絕該訂單，則有機會將產能留給製造未來可以帶來更高利潤的訂單。
本研究運用Hung and Lai (2010)提出之模擬期望收益決策步驟法，解決產能配給問題。根據實驗的結果，此方法相較於不考慮配給的先來先服務政策，利潤高出約3.98%；此外，在改變問題控制因子下，模擬期望收益決策步驟法的表現相較於先來先服務政策均較佳。總體而言，模擬期望收益決策步驟對於隨機環境下的訂單選擇問題是一個有效的方法。
關鍵字：產能配給；普瓦松過程；決策支援系統

This study focuses on a capacity rationing problem for make-to-order manufacturing, in which the allocation of finite capacity to various random inquiry orders from Poisson processes has to be determined. In make-to-order manufacturing environments, future orders with varying ready dates, due dates, processing times, and profits arrive randomly. With the objective of maximizing profit, a manufacturer should make the acceptance-or-rejection decision immediately when an order request arrives. If the manager accepts an order, the remaining capacity is reduced and the profit of the order is earned. On the other hand, if the manager rejects the request, the capacity is reserved and could be probably utilized to produce higher profit orders arriving in the future. This study focuses on such a stochastic rationing decision problem.
A dynamic decision method called simulated expected revenue decision procedure (SER) proposed by Hung and Lai (2010) is adopted in this study to deal with the capacity rationing problem. This study conducts the simulation experiments to compares the results of SER, first-come-first-served (FCFS), and a decision criterion based on loading estimation. According to the experiment results, SER outperforms FCFS by an average profit of 3.98%. Besides, under various problem conditions, the performance of SER is more robust than FCFS. Therefore, SER is an effective decision method for the MTO capacity rationing problem.
Keywords: capacity rationing; Poisson process; decision support system.

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