在本篇研究提出兩個生產規劃模型，用以求解案例太陽能製造公司做生產規劃時，所面對的未來需求不確定性。該案例公司的生產目標是要決定該公司生產原料的購買種類和購買量，以及產品的生產種類和生產量，並藉此將收益最大化。然而，需求的不確定性使得決策難以制定。許多確定性模型被用來求解生產規劃問題。在不確定性較為顯著的環境中，利用確定性的模型所求得的生產規劃是否穩健，是令人存疑的。因此，需要發展考慮不確定性的隨機性模型。這篇研究提出確定性與隨機性這兩個模型，用以求解考慮需求不確定下，案例太陽能電池製造公司的生產規劃問題，並且透過實驗比較這兩個生產規劃模型的長期效益。
滾動平面法是一個在實務上常用的生產規劃法，也就是在每一期的期初都對生產規劃做出修正。本篇研究在考慮滾動規劃期的環境下，模擬確定性模型與隨機性模型，並利用許多不同的因子組合比較成效。在實驗中，我們利成對樣本t檢定去比較確定性模型與隨機性模型兩者間是否在統計上有顯著的差異。

This study proposes two production planning models for a case study solar cell manufacturing company who faces uncertain future demands. The objective of the case study company is to determine which and how many materials should be purchased and which and how many products should be produced with the objective of maximizing net profit. However, uncertain demands make the planning problem difficult. Many deterministic production planning models are used to solve the production planning problem. In a significantly uncertain environment, it is questionable that a deterministic model could drive robust plans. Therefore, it could be necessary to develop stochastic models that consider uncertainties. This study proposes two production planning models, a deterministic model and a stochastic model, to solve a production planning problem for a case study solar cell manufacturing company with demand uncertainty and compares their long-term effectiveness via simulation experiments.
A common practice production planning is called rolling horizon, in which production plan is revised at the beginning of each period. This study simulates the deterministic model and stochastic model under rolling planning horizon environment and compares their performances under a number of control factors. At the end of the experiments, a paired -test is used to compare whether the long-term profit of these two production planning models are statistically significantly different.

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