多產品隨機價量函數下之動態產能規劃

吳政鴻Wu, Cheng-Hung臺灣大學:工業工程學研究所李依玲Li, Yi-LingYi-LingLi2010-05-032018-06-292010-05-032018-06-292009U0001-2607200914565400http://ntur.lib.ntu.edu.tw//handle/246246/178527本研究以企業產能規劃為主軸，提出一多重價位模型動態產能規劃求解之。有別於傳統產能規劃，本模型試以不同面相觀察多重價位產品對產能規劃造成之影響，並於研究中強調多價位產品間對應相異需求曲線的存在，以及利用馬可夫性質描寫企業面臨需求環境變動之特性。中利用動態規劃求解長期、各產能水準及各需求環境狀態下之最佳產能擴充量，以Microsoft Visual C#語言撰寫迭代演算式輔助求解，並將結果輸出於Microsoft Office Excel中分析。為證明模型之合理性與可行性，文章中提出一ASP（平均售價模型）做為參照，比較兩模型於多組需求情境參數下之績效。由實驗中可得知模型在參數變動下對決策行為之影響，及兩模型之決策差異，歸納出依照多重價位模型決策確實可得到較ASP佳之收益表現。In our research, we focus on the industry capacity planning, using a multi-priced products dynamic capacity planning to solve it. The main difference between our model and traditional capacity planning is that we try to describe the impact caused by multi-priced products on capacity planning, emphasize the existence of distinct demand functions of different-priced products, and use Markov property to picture the stochastic demand environment faced by industries.n context we use dynamic planning to solve the best capacity increment quantities under different states, like different periods, capacity levels and demand environments. Exploit Microsoft Visual C# to help us calculate the iteration algorithm parts, and output the results to Microsoft Office Excel for analyses. In order to prove the rationality and feasibility of our model, we use ASP model (average selling price model) to be a comparison, so that we can compare their effects under multiple demand environment parameters. According to the results, we can observe the decision behaviors under variant parameters, and the difference between two models, so we can conclude that following the multi-price model decision policy can result better revenue than ASP model.誌謝 i文摘要 iibstract iii錄 v表目錄 vi格目錄 vii 1 章緒論 1.1 研究背景 1.2 研究動機與目的 3.3 研究步驟 8 2 章文獻回顧 10.1 問題特性 10.2 數學求解方法 14.3 近期產能規劃文獻 16.4 小結 18 3 章模型建立 19.1 問題描述 19.2 問題假設 21.3 動態規劃模型 22.3.1 決策時程 23.3.2 狀態 24.3.3 決策 25.3.4 機率 25.3.5 回饋 26.3.6 迭代演算法 28.4 ASP模型 29 4 章模型評估 33.1 績效驗證方法說明 33.2 多組環境測驗 37.3 驗證結果彙整 49 5 章結論與未來展望 51.1 結論 51.2 未來研究方向 52考文獻 53application/pdf1651615 bytesapplication/pdfen-US產能規劃動態規劃多價位產品平均銷售價格Capacity planningdynamic planningmulti-priced productsaverage selling price多產品隨機價量函數下之動態產能規劃Dynamic Capacity Planning Under Multi-Products Stochastic Price-Demand Functionsthesishttp://ntur.lib.ntu.edu.tw/bitstream/246246/178527/1/ntu-98-R96546003-1.pdf