臺灣博碩士論文加值系統

發生大規模災害後，可能會同時在多個地方發生事故，而每事故點若有大量傷患的話，如何有效率地使用有限的救護車資源，將各事故點的傷患儘快送至合適的醫院便成為一個重要議題。現今由緊急醫療救護系統之救護車指揮中心所調度的救護車派遣方式，通常是取決於決策者的自身經驗，其直覺的派遣決策缺乏整體性的評估，可能導致傷患等待過久而死亡。本研究擬探討緊急醫療救護系統面對多事故點的大量傷患之救護車派遣問題，以最小化傷患總等候時間為目標，決定哪台救護車應去哪個事故點將傷患送至哪家醫院的最佳派遣路徑。本研究依救護車之初始位置狀態，分別研究「已知初始發車處」及「可彈性調整初始發車處」等兩類救護車派遣問題。兩者皆假設各事故點位址及其傷患數量、各醫院位址等資訊皆已知，只是前者假設各救護車發車處為已知，著重在如何計算車輛途徑；而後者則假設各救護車初始發車處可彈性調整，除了車輛途徑決策外還必須處理初始的車輛配置方式（每個事故點應配置幾台）。
在求解已知初始發車處之救護車派遣問題時，我們先以時空網路圖為基礎發展一整數規劃模式，求解最小化傷患總等候時間的救護車最佳路徑，然而此種作法經常耗時甚久，因此我們提出以傷患找尋最近救護車的貪婪演算法；而為避免派遣決策過度集中處理單一事故點而忽略其它事故點傷患，我們亦提出另一考量「公平性」的派遣演算法來比較。可彈性調整初始發車處之救護車派遣問題主要是著眼於現實的派遣決策幾乎無法即時使用電腦求解，而較直覺的派遣決策通常會以事故點與醫院之責任劃分方式來指派救護車，因此該如何指定哪些醫院負責哪些事故點，再依此指派各醫院的初始救護車數，以最小化傷患總等候時間。
最後本研究針對兩問題中建構出8個與24個不同的Case進行測試，證實本研究之數學模式可有效地使傷患總等候時間最小化，而提出之演算法亦能在短時間內得到求解品質佳的解。

The aim of this study included developing mathematical models of optimal ambulance redeployment for shipping mass casualties in an emergency medical services system by using integer programming. Additionally, the objectives of the study involved minimizing the total waiting time for casualties. In the study, two ambulance redeployment problems, namely (1) Ambulance Dispatching Problem with the Initial Location provided, and (2) Ambulance Dispatching Problem with a Flexible initial Location, were investigated. It was assumed that the number of event points, hospitals, and patients were given for both problems. Although both problems required solving for optimal ambulance routings, the latter problem focused more on initial ambulance deployment. An integer programming model was formulated on a time space network for the first problem. However, the model was extremely time consuming. This was followed by developing a greedy heuristics based on a nearest first concept, in which the ambulance closest to a casualty was assigned to the casualty. In order to derive a fair waiting time, another heuristics that allowed each casualty to have a more equal waiting time was also employed. With respect to the second problem, certain properties of optimal redeployment were first derived for a hospital case, and then greedy heuristics were derived for other general cases. Unfortunately, a specific relationship between the optimal number of ambulances and the distance of the number of casualties to event points could not be derived from the results of the study.

目錄

摘要 I
ABSTRACT II
誌謝 VI
目錄 VII
表目錄 XI
圖目錄 XII
第一章 緒論 1
1.1研究背景 1
1.2研究動機與目的 3
1.3研究問題 4
1.4論文架構 5
第二章 文獻探討 6
2.1緊急醫療救護系統與大量傷患事件 6
2.1.1緊急醫療救護服務系統 6
2.1.2大量傷患事件 8
2.2救護車派遣與緊急醫療救護系統佈署問題 10
2.2.1 救護車基地佈署問題 10
2.2.1.1確定性靜態佈署模式 10
2.2.1.2隨機性靜態佈署模式 14
2.2.1.3動態佈署模式 16
2.3救護車輛派遣問題 17
2.4小結 21
第三章 已知初始發車處之救護車派遣問題 22
3.1問題描述與相關假設 22
3.1.1問題描述 22
3.1.2問題假設 25
3.2數學模式 25
3.2.1已知初始發車處之救護車派遣之時空網路圖模式 25
3.3貪婪演算法與傷患平衡之救護車派遣法 30
3.3.1 演算法介紹 30
3.3.2 演算法介紹 34
3.3.3小結 36
3.4數值分析 36
3.4.1數據產生方式 36
3.4.2數值測試 38
3.4.3小結 42
第四章 可彈性調整初始發車處之救護車派遣問題 44
4.1問題描述與假設 45
4.1.1問題描述 45
4.1.2問題假設 45
4.2時空網路圖之救護車派遣整數規劃模式( ) 46
4.2.1參數與變數定義 46
4.2.2模式說明 47
4.2.3範例說明 49
4.3順序式救護車派遣之整數規劃模式( ) 52
4.3.1基本概念 52
4.3.2參數與變數定義 53
4.3.3順序式模式說明 54
4.3.4範例說明 55
4.4貪婪演算法 58
4.4.1基本想法 58
4.4.2 、 演算法說明 60
4.5數值分析 66
4.5.1數據產生方式 66
4.5.2數值測試 67
4.5.3小結 74
第五章 結論與未來方向 76
5.1研究結論 76
5.1.1已知初始發車處之救護車派遣問題 76
5.1.2可彈性調整初始發車處之救護車派遣問題 77
5.2未來研究方向 77
參考文獻 81

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