本研究主要是探討台灣血液供應鏈之區位定址問題，依據退化性產品(血液)之特性區分為兩階段討論本研究的數學模型，策略階段為整合供應鏈管理議題中定址與運輸問題；戰術階段則是庫存控制問題，以兩階層的供應鏈為例，由捐血中心將血液產品運送至血液倉儲，血液倉儲再將血液產品配送至各層級醫院。
本模式所考量的目標為總供應鏈成本最小與服務回應率最大，因研究模式為多目標模式，所以本研究使用基因遺傳演算法（NSGA-Ⅱ）求解混合非線性整數規劃問題，並以兩個貪婪法則運用基因遺傳演算法求取柏拉圖最佳解。
依據所欲研究問題之混合式基因遺傳演算法所建立的MATLAB程式進行相關模式求解與數據分析，瞭解數學規劃模式中相關參數與不同因子之間的變化，對整個整合性血液供應鏈網路選址問題中最適解的影響。
最後，本研究從台北捐血中心所負責之各層級醫院中找出15家潛在血液倉儲的實際位置，由設計三種個案情境將不同目標函數賦予三個不同權重數值，得知不同目標函數權重之情境明顯影響血液倉儲地點設置與數量的決策，求解出每個血液倉儲最適補貨週期與經濟訂購量，並以敏感度分析來探討各項成本的影響程度，而此研究結果可提供於決策者最適選擇方案。

The study is focused on the design of Facility Location Problem (FLP) in a logistics network for a blood supply chain in Taiwan. According to the blood characteristic of deterioration, we design a two-staged model to depict our problem. In the strategic level, we discuss the issues of facility location and transportation decisions in supply chain management. In the tactic level, we consider about the inventory control problem. In our two-staged blood supply chain, the blood center, where the blood is collected from donors, sends whole blood to a blood warehouse and then it is distributed to different levels of hospitals.
Our goal of using two objectives to minimize the total supply chain cost and the maximize responsiveness level. In order to find the Pareto optimal solutions, we use Non-dominated Sorting Genetic Algorithm (NSGA-Ⅱ) to solve a mixed nonlinear integer programming problem with two greedy heuristics. We use the software of MATLAB to solve our established model. According to the computational results, we realize the effects of the optimal Pareto solutions in our problem.
We also design three different scenarios to understand how different conditions affect both strategic and tactic decisions so that, the decision makers could make decisions from the computational solutions. Finally, we perform sensitivity analysis to understand the impacts on changing model parameters.

目 錄
目錄	I
表目錄	III
圖目錄	IV
第一章 緒論	1
1.1研究背景與動機	1
1.2研究目的	5
1.3研究範圍與限制	6
1.4研究流程與架構大綱	8
第二章 文獻探討	11
2.1研究問題文獻	11
2.1.1退化性產品	11
2.1.2供應鏈管理模式	16
2.1.3血液供應鏈管理	30
2.2研究方法文獻	40
2.2.1多目標規劃法	40
2.2.2多目標遺傳演算法	49
2.3小結	57
第三章 血液供應鏈模式建構	58
3.1研究問題描述	58
3.1.1美國Chicago地區之區域血液供應鏈現況	58
3.1.2台灣地區之區域血液供應鏈現況	59
3.1.3本研究之研究問題	60
3.2研究問題建構	65
3.2.1研究假設論述	65
3.2.2研究模型符號說明	66
3.3小結	77
第四章問題求解方法	78
4.1多目標最佳化方法介紹	78
4.1.1多目標問題定義	78
4.1.2多目標基因遺傳演算法	79
4.2概述第二代非支配基因演算法（NSGA-Ⅱ）	80
4.2.1NSGA-Ⅱ相關背景與基本運算規則	80
4.2.2基因遺傳演算法求解數學模型	83
4.3小結	87
第五章 個案設計與分析	88
5.1個案設計說明	88
5.1.1相關資料論述	89
5.2個案求解	91
5.3個案分析	93
5.3.1階段一策略定址設計模型	93
5.3.2階段二戰術庫存規劃模型	109
第六章	結論與後續研究建議	121
6.1研究結論	121
6.2管理意涵	122
6.2.1學術管理意涵	123
6.2.2實務管理意涵	123
6.3後續研究建議	125
6.3.1資料蒐集	125
6.3.2研究方法	125
6.3.3逆物流血液回收管理	126
6.3.4急難供應鏈管理	126
6.3.5資料倉儲與RFID	127
參考文獻	128
附錄一	143
 
 
表目錄
表2-1 退化性商品的分類	12
表2-2 非立即退化問題的相關文獻整理	15
表2-3 區位定址問題之數學分析方法	19
表2-4 設施區位問題與銷售物流網路之相關研究文獻整理	21
表2-5 位置庫存模型分類	27
表2-6 不同國家人口血型比例	32
表2-7 研究方法相關文獻整理	36
表2-8 分類層級相關研究文獻整理	38
表2-9 多目標規劃法相關研究文獻整理	42
表2-10常見的傳統多目標規劃法整理	44
表2-11多目標遺傳演算法分類表	54
表3-1 策略階段相關成本結構分析	69
表4-1 兩種貪婪法則說明	84
表5-1 相關參數假設資料說明	90
表5-2 柏拉圖最適解之演進趨勢圖與圖形說明	92
表5-3 標準化表示法	94
表5-4 個案情境論述	95
表5-5 柏拉圖前緣解與計算決策結果	96
表5-6 不同情境所對應之目標函數值與血液倉儲設置數	100
表5-7 三組柏拉圖最適前緣解之差異性比較	100
表5-8 不同情境下的柏拉圖最佳解與對應醫院結果	101
表5-9 柏拉圖前緣解之總供應鏈成本項目比重	105
表5-10 三組柏拉圖最適前緣解之成本結構分析	108
表5-11 庫存規劃階段確定性庫存模式符號假設	109
表5-12 血液倉儲與所對應醫院之年血液需求量	111
表5-13 倉儲最適補貨週期、經濟訂購量與庫存相關成本	117
表5-14 不同參數變動下對最適解的影響	118
 
圖目錄
圖1-1 台北捐血中心血液配送模式	4
圖1-2 設置血液倉儲後配送模式	5
圖1-3 本研究的研究流程	8
圖2-1 供應鏈領域	16
圖2-2 銷售網路設計系統中之四個戰略計劃	21
圖2-3 供應鏈管理模式	24
圖2-4 整合性供應鏈模式	24
圖2-5 三階層系統	26
圖2-6 區域性血液供應與需求圖	31
圖2-7 血液管理研究文獻趨勢圖	34
圖2-8 血液管理的解決方法趨勢圖	35
圖2-9 血液管理的分類層級趨勢圖	38
圖2-10 精確式解法與啟發式解法研究文獻趨勢圖	40
圖2-11 多目標規劃法之分類	43
圖2-12 雙目標最小化柏拉圖最適解集合	48
圖2-13 多目標遺傳演算法分類圖	49
圖3-1 地區性血液供應鏈的分類層級架構	59
圖3-2 台灣區域血液的作業配送流程	60
圖3-3（1-3）不同組織架構之血液供應模式	61
圖3-4 本研究之血液供應鏈網絡系統架構圖	62
圖3-5 概述本研究的策略定址設計和戰術庫存規劃流程	63
圖3-6 數學模型的概念圖形	67
圖3-7 概述階段一總供應鏈之成本結構	68
圖3-8 集合覆蓋問題	70
圖3-9 部分欠撥且欠撥率與等候時間相關之非即時退化物品庫存系統	75
圖4-1 典型的基因遺傳演算法架構	79
圖4-2 非支配解的排序過程	81
圖4-3 擁擠距離推測	82
圖4-4  NSGA-Ⅱ的演算流程	82
圖4-5 研究問題之基因編碼方式	83
圖4-6 混合基因演算法流程圖	85
圖4-7 均一交配的範例說明	86
圖5-1 研究個案之物流配送架構圖	89
圖5-2 個案情境分析	95
圖5-3 CASE 1平均目標最適解選址結果	103
圖5-4 CASE 2成本最適解選址結果	104
圖5-5 CASE 3服務回應最適解選址結果	104

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三、網路資料
1.中華民國內政部全球資訊網，取自：http://www.moi.gov.tw/index.aspx。
2.台灣血液基金會-台北捐血中心，取自：http://www.tp.blood.org.tw。
3.維基百科，取自：http://zh.wikipedia.org。