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系統識別號 U0026-0607201412183100
論文名稱(中文) 遇缺補貨型動態(s, Q)存貨政策之解法發展
論文名稱(英文) Efficient Heuristics for Solving Dynamic (s, Q) Inventory Problem with Backorder
校院名稱 成功大學
系所名稱(中) 工業與資訊管理學系
系所名稱(英) Department of Industrial and Information Management
學年度 102
學期 2
出版年 103
研究生(中文) 柯建廷
研究生(英文) Jian-Ting Ke
學號 R36024095
學位類別 碩士
語文別 中文
論文頁數 63頁
口試委員 指導教授-李賢得
口試委員-利德江
口試委員-吳植森
中文關鍵字 動態需求  (s, Q)存貨模式  遇缺補貨  啟發式解法 
英文關鍵字 dynamic inventory problem  (s, Q) policy  backorder  heuristic  complexity 
學科別分類
中文摘要   本研究探討面對動態需求之遇缺補貨(s, Q)雙櫃型存貨政策,問題中已知未來固定規劃期間內之各期顧客需求量,如顧客訂單或預測之需求量,在每次訂購成本、單位採購成本、單位存貨持有成本、單位缺貨成本和前置時間皆為已知的情形下,決定其最佳之存貨決策。該系統之運作情形如下:在每期期初檢查庫存水準是否低於訂購點s,若是則進行訂購作業,每次訂購量為固定Q,並於經過固定之前置時間後,在期初到達;若否,則不進行訂購作業,當缺貨發生時,則以遇缺補貨的方式處理,即當期未能滿足之顧客需求,可於經過前置時間後,在所訂購的產品到達時立即優先補足。
  本研究之目的為發展快速求解方法,以求得最佳或近似最佳訂購點與固定訂購量,使得規劃期內的總成本為最小,總成本包含訂購成本、採購成本、存貨持有成本與缺貨成本。針對此動態型存貨問題,本研究首先建立動態規劃數學模式,並根據問題特性與古典動態批量理論,發展最佳解理論性質,並透過最佳解性質與歸納法則發展出兩種可於多項式時間內求解的啟發式演算法,時間複雜度分別為Ο(N^5)與Ο(N^3),N為規劃期之大小。演算實驗發現,第一種解法之求解品質優異,與窮舉法之最佳政策比較,大部分問題皆可求得最佳解,僅在極少數特殊情形才可能求得非最佳解;在第二種較快速之解法,其求得最佳解之比例接近百分之九十八,與最佳政策比較,其總平均成本偏差小於0.1%,故整體求解品質表現上亦屬優異,實驗中發現當平均需求速率較大、總規劃期數較大以及遇缺補貨成本較低時,此啟發式解法之求解品質較佳亦較穩定。
英文摘要   A dynamic (s, Q) inventory policy with backorder is addressed in this thesis. Given a stream of demand data for a finite period, the reorder point (s) and fixed order quantity (Q) are to be determined to minimize the sum of ordering cost, unit variable cost, inventory carrying cost, and cost due to backorder. The dynamic (s, Q) policy can be stated as below: starting with inventory of (s+Q), we examine the inventory position at the beginning of each period. If the inventory position falls below the reorder point, an order of quantity Q will be placed and it will arrive after the constant lead time. Any shortage is backordered and filled as soon as the new stock from replenishment is available.
  The dynamic inventory problem can be formulated as a dynamic programming model. Two dominance properties are discovered, and are used to develop two efficient heuristics, which run in polynomial time.
  Computational experiments and results have shown that both heuristics perform pretty well. The K-order quantity heuristic gives superior solution quality with complexity Ο(n^5), where n is the number of planning periods in the dynamic inventory problem. The second heuristic with complexity Ο(n^3)-flow-balance heuristic which is more efficient than the first one also performs very well. The heuristic finds optimum policy for over 98% of the data set, and the deviation of total cost from those in the optimization model is less than 0.1%.
論文目次 摘要.................................................... I
Extended Abstract...................................... II
誌謝.................................................... V
目錄.................................................... VI
表目錄................................................... VIII
圖目錄................................................... IX

第一章 緒論.............................................. 1
1.1研究動機............................................ 1
1.2研究目的............................................ 1
1.3研究範圍與限制....................................... 2
1.4研究架構與流程....................................... 2
第二章 文獻回顧........................................... 5
2.1古典存貨理論模式..................................... 5
2.2存貨政策............................................ 7
2.3動態存貨控制模式..................................... 13
2.3.1古典動態批量模式................................. 13
2.3.2二階層動態批量模式................................ 15
2.3.3單階層動態型(s, S)庫存模式........................ 16
第三章 動態型(s, Q)庫存模式與理論特性發現..................... 19
3.1問題描述............................................ 19
3.2動態規劃模式......................................... 21
3.3最佳解理論性質之發現與證明............................. 23
第四章 啟發式解法發展與演算實驗.............................. 33
4.1啟發式演算法發展..................................... 33
4.2演算範例說明......................................... 39
4.2.1應用動態規劃原理求解(精確最佳解).................... 39
4.2.2應用啟發式演算法求解.............................. 40
4.3演算實驗............................................ 44
第五章 研究成果與未來建議................................... 48
5.1研究成果............................................ 48
5.2未來建議............................................ 49
參考文獻................................................. 50
附錄A.1:演算法之程式碼.................................... 54
附錄A.2:產生規劃期內隨機需求量之程式碼(Poisson隨機變數)........ 61
參考文獻 中文文獻:
林開正,銷售損失(s, S)庫存系統-確定型最佳解與分配型近似解之研究,國立成功大學工業管理研究所碩士論文,民國八十五年六月。

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