本研究之產能規劃以一生產多產品之供應鏈為主軸,由上游廠商提供半成品給下游廠商加工製造成成品銷售,各產品族於各階段之產能需求量具差異,市場需求視為上游及下游之需求。依據不同的消費者需求進行差異定價,當企業面對的需求市場需求具不確定性時,利用動態規劃的方式,求解各期、各種產能水準及需求環境下之最佳產能分配及擴充決策。 文中以三種情境來定義不同的需求環境,各以一線性函數描述需求量與價格之間的相依性,利用馬可夫性質描寫需求環境變動的特性。求解及模擬的部分皆以撰寫Visual C#程式語言來輔助,將結果輸出至Excel作分析。 為證明本研究模型之合理性及穩健性,以另一模型(ASP[平均售價模型))作參照,以模擬的方式比較多重價位模型之決策差異及績效表現。結果顯示出,在收益表現上,多重價位模型皆優於ASP模型。
In this research, we present a dynamic programming approach to capacity planning under demand uncertainty. Demand is dependent on time and price. We define 3 demand scenarios which are formulated as linear functions and describe them with Markov property. We can have a series of capacity expansion policy which the long term profit is maximized subjected to floor space and budget constraint. We focus on the impact of multi-price model in an industry which has several process stages and produce multiple products. In order to prove the robust of our model, we compare it to ASP (Average Selling Price) model. And the result shows that multi-price model always has better performance in profit than ASP model.