啤酒需求具有不確定性與季節變化之特性。過去以需求預測與半成品庫存評估投料量，未仔細安排生產排程之最佳時機，導致供需難以平衡。本研究由收集歷史銷售資料推估需求分配，並藉由統計方法區分淡旺季之需求，並利用最佳化技術尋找當季每週最適生產量以達期望總利潤最大化之目標。根據每週最適生產量，建構混合整數線性規劃模型，求解最適生產排程，以達總生產損失最小化之目標，提升生產排程之品質，最後以實際案例驗證模式之可行性與效率性。

Demand of beer is uncertain and has seasonal fluctuation. Over the past years, based on demand forecast and quantity of semi-finished product to assess the input amount of materials, and have not evaluated the optimal production time, so it was difficult to balance the demand and supply. This research is based on historical data to infer the demand distribution, and applied statistical cluster analysis technique to classify the off-season and season demand. We applied the optimization technique to search for an optimal production quantity to maximize the total expected profit. We also establish a mixed-integer linear programming model for production scheduling to minimize the total production losses according to the given production quantity per week. Therefore, the quality of production scheduling was improved. Finally, this paper takes a real case to demonstrate the validity of the proposed model.