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系統識別號 U0026-2301201505083000
論文名稱(中文) 混沌需求下血液存貨管理模式之研究
論文名稱(英文) An Inventory Management Model for Blood Product with Chaotic Time Series Demand
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 103
學期 1
出版年 104
研究生(中文) 陳慧如
研究生(英文) Huei-Ru Chen
學號 R36014155
學位類別 碩士
語文別 中文
論文頁數 64頁
口試委員 指導教授-王泰裕
口試委員-施勵行
口試委員-陳梁軒
口試委員-張權發
口試委員-謝中奇
中文關鍵字 血液  醫院血液存貨管理  混沌需求  混沌時間數列 
英文關鍵字 perishable inventory  blood inventory management  chaotic demand  chaotic time series 
學科別分類
中文摘要 血液為ㄧ種具有固定有限壽命之易腐性產品,由於其有限壽命的產品特性,會使得當血液庫存過多時,血液未能在壽命期限前被使用而造成過期,必須將血液報廢,因而產生了不必要的社會資源浪費;反之,由於血液為醫療過程中的一項重要資源,若血液庫存過少時,血液的短缺則會造成醫院服務水準下降且提高了病患之風險。現今許多已開發國家的社會人口結構的改變,造成了血液資源上,捐血量降低的可能性,而血液需求量卻隨著人口老化而快速增加。在上述之情形下,可以了解到有效管理可取得的血液資源是社會上相當重要之議題。
由於在臨床上血液的需求難以確定,在過去的研究中通常將血液需求視為隨機性,但是近年來隨著非線性確定性動態系統的混沌理論之發展,發現到自然界和社會中許多現象皆具有混沌性質,雖然其看似混亂、隨機且無規則可循,但實際上其變化具有某種型態之運行軌跡。且文獻中亦曾驗證了血液供應鏈的每日需求量具有混沌性質,因此本研究欲將此性質納入醫院之血液需求預測,以更貼近血液需求的動態變化,提供更精確的資訊,提升血庫的存貨管理績效。
本研究考量實際血液需求時間數列具有混沌特性,接著利用混沌預測方法與ARIMA模型預測需求量,並比較其結果,最後,建立一個醫院血液存貨管理的訂購決策模式,以供血庫管理者評估當前血庫存貨狀態、可能之需求量以及捐血中心供應的血液年齡狀況下,制定一個最佳目標存貨水準以最小化血液存貨成本。透過實際血小板需求序列進行模式驗證,並求得其最佳目標存貨水準,於參數分析中發現,若血液的供應年齡不易造成過期血液,則決策變數的結果對於此因素的敏感度不大;若容易造成過期血液,則其敏感度大。固定血液年齡供應情形時,單位持有成本對於決策變數所造成的影響最大,而決策變數對於單位缺貨與過期成本的敏感度不大。
英文摘要 Blood is not only a crucial resource in hospital but also a perishable product. Therefore blood inventory management is a trade-off between shortage and wastage (expired blood). Nowadays, demographic structures for many countries have changed. Good inventory management for blood products is more and more important because blood products demand is increasing and blood donation is decreasing. The main reasons for this phenomenon are the aging population and decreasing birth rate. This is especially important in the area using blood donation as main blood sources such as Taiwan. Since the blood demand is uncertain, researchers use probability distribution to describe the blood demand in previous studies. As the deterministic nonlinear chaotic dynamic system evolved, many researchers found that there are many chaotic phenomena around our environment. In this study, the chaos characteristics of a real blood product demand is examined by the value of maximal Lyapunov exponent. Besides, a comparison study between chaotic time series method and ARIMA model is conducted for their forecasting performance. Furthermore, a decision model includes shortage, expired and holding cost for blood product inventory management in a hospital is implemented to minimize the cost of blood product inventory. In this proposed model, the state of inventory, future demand and freshness of blood which supplied by blood center are taken into account to set up the optimal order-up-to level. Finally, a real demand of platelet from a hospital is provided to verify the appropriation of this model. In addition, the sensitivity analysis is conducted to determine the influences of different parameters with regard to total cost and the optimal order-up-to level. The results show that there is no significant difference between two methods of demand forecasting. The freshness of supplied blood product is very sensitive to the optimal order-up-to level. If the freshness of blood product are the same from the supply side, the holding cost per unit is more sensitive than the shortage and expired cost per unit to the optimal order-up-to level.
論文目次 中文摘要 i
英文摘要 ii
致謝 ix
目錄 x
表目錄 xii
圖目錄 xiii
第一章 緒論 1
第一節 研究背景與動機 1
第二節 研究目的 2
第三節 研究範圍與限制 3
第四節 研究流程 4
第五節 論文架構 5
第二章 文獻探討 6
第一節 易腐性存貨 6
第二節 血液存貨管理 8
第三節 混沌理論 13
第四節 時間序列分析 24
第五節 小結 27
第三章 混沌需求下血液存貨管理模式 29
第一節 問題描述 29
第二節 模式假設與參數符號 32
第三節 血庫存貨成本模式建立 34
第四節 血庫存貨成本模式求解 39
第五節 小結 40
第四章 模式驗證與分析 42
第一節 個案醫院資料簡介 42
第二節 需求時間數列之混沌性質分析 43
第三節 需求時間序列之預測 45
第四節 存貨決策模式之實例驗證與分析 49
第五節 敏感度分析 52
第六節 小結 56
第五章 結論與建議 57
第一節 結論 57
第二節 未來研究方向 58
參考文獻 60
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