台灣位於西北太平洋的亞熱帶地區，且颱風頻繁，加上地形坡陡、川短流急，對於颱洪期間如何有效操作水庫之效益，以達到水庫蓄水與防洪減災為重要課題。在多水庫同時進行水庫防洪操作時，需考慮洪水洩放歷程，以避免造成下游匯流口發生嚴重人為失當引發的洪災問題；因此，本研究在探討多水庫聯合防洪操作之規劃，除考慮各水庫的防洪與蓄水之功能外，並考慮下游匯流口之洪水歷程。
本研究以多水庫操作最佳化為目標，運用多水庫防洪操作運轉辦法及相關水庫硬體限制建立防洪運轉模式，以搜尋多水庫防洪最佳洩放歷程，利用非優勢排序遺傳演算法(Non-dominate Sorting Genetic Algorithm , NSGA-II)搜尋水庫最佳洩放歷程，探討水庫操作之合理性。本研究以石門與翡翠兩水庫系統以及該匯流處為研究對象，以非優勢排序遺傳演算法搜尋之結果顯示將有效達到洪峰消減並儲存洪水以滿足期末水位以利未來供水運用。

Taiwan is located in the Northwestern Pacific Ocean subtropical jet stream monsoon district and frequently hit by Typhoon. Because the steep mountainous landform makes most of the rainfall flow immediately into the ocean with a few hours, the river cannot keep enough water for future use. Reservoirs have become the most import and effective floodwater storage facilities. The huge flood often exceeds the capacity of the reservoirs; consequently, attention must focus on improving the operational effectiveness and efficiency of existing reservoirs for maximizing the beneficial use of water storage and decreasing the flood peak stage downstream. Especially, for the flood operation of the multi-reservoir system, it should prevent the downstream from a serious man-made flood. 
This study proposes a multi-reservoir flood operation optimization model with linguistic flood control requirement and existing operational regulations for providing the information of rational multi-reservoir flood operating decisions. The approach involves formulating multi-reservoir flood operation as an optimization problem and using the non-dominate sorting genetic algorithm (NSGA-II) as searching engines. The proposed approach was applied to the problem of finding the optimal release and desired storage, taking the multi-reservoir system of Shihmen and Feitsui reservoirs as a case study. The decrease rates of flood peak of two reservoirs and the junction are considered as the multi-objective functions. The results demonstrated that NSGA-II could effectively provide rational flood operating decisions of the multi-reservoir system to reduce flood damage during typhoon periods and to increase final storage for future usages.

謝誌	I
中文摘要	II
ABSTRACT	III
章節目錄	V
表目錄	VIII
圖目錄	IX
一、前言	1
1.1研究動機	1
1.2研究目的與方法	2
二、文獻回顧	3
2.1遺傳演算法的應用	3
2.2水資源方面的應用	3
三、理論概述	6
3.1遺傳演算法	6
3.1.1遺傳演算法之基本架構	7
3.2非優勢排序遺傳演算法	7
3.2.1非優勢排序遺傳演算法之基本元素與運算子	10
3.2.2多目標遺傳演算法之特性	14
四、研究案例	16
4.1水庫簡介	16
4.1.1石門水庫簡介	16
4.1.2翡翠水庫簡介	17
4.1.3匯流口簡介	17
4.2水庫防洪操作	18
4.2.1石門防洪運轉操作規則	18
4.2.2翡翠防洪運轉操作規則	19
4.2.3相關水利法規	20
4.3颱風資料蒐集與分析	20
4.4多水庫聯合防洪操作之決策模式	22
4.5非優勢排序遺傳演算法（NSGA-II）	28
4.5.1運算方法及相關參數設定	28
4.5.2搜尋範圍設定	29
4.5.3結果	31
4.5.4改變初始水位搜尋之結果	48
五、結論與建議	50
5.1結論	50
5.2建議	51
參考文獻	53
附錄Ａ 石門水庫以NSGA-II搜尋之洩放趨勢圖	57
附錄B 翡翠水庫以NSGA-II搜尋之洩放趨勢圖	67
表目錄
表4.1石門與翡翠水庫颱風資料	21
表4.1石門與翡翠水庫颱風資料（續）	22
表4.2相關設定參數	28
表4.3歷時40小時的颱風限制式個數	28
表4.4 石門與翡翠水庫於NSGA-II與原操作之防洪操作結果比較	32
表4.4石門與翡翠水庫於NSGA-II與原操作之防洪操作結果比較（續）	33
表4.5 匯流口NSGA-II與原操作之洪峰消減率比較	33
表4.5 匯流口NSGA-II與原操作之洪峰消減率比較（續）	34

圖目錄
圖3.1 Pareto鋒線示意圖	8
圖3.2 非優勢排序遺傳演算法流程圖	9
圖3.3 實數編碼組成之範例	10
圖4.1兩水庫系統與下游匯流口位置圖	18
圖4.2石門水庫運轉規線示意圖	24
圖4.3翡翠水庫運轉規線示意圖	24
圖4.4洪峰發生前後階段區別示意圖	27
圖4.5碧利斯颱風（石門）搜尋之洩放量與水庫水位趨勢圖	36
圖4.6碧利斯颱風（翡翠）搜尋之洩放量與水庫水位趨勢圖	37
圖4.7 歐馬颱風（石門）搜尋之洩放量與水庫水位趨勢圖	38
圖4.8歐馬颱風（翡翠）搜尋之洩放量與水庫水位趨勢圖	39
圖4.9賀伯颱風（石門）搜尋之洩放量與水庫水位趨勢圖	40
圖4.10賀伯颱風（翡翠）搜尋之洩放量與水庫水位趨勢圖	41
圖4.11艾利颱風（石門）搜尋之洩放量與水庫水位趨勢圖	42
圖4.12艾利颱風（翡翠）搜尋之洩放量與水庫水位趨勢圖	43
圖4.13納莉颱風（石門）搜尋之洩放量與水庫水位趨勢圖	44
圖4.14納莉颱風（翡翠）搜尋之洩放量與水庫水位趨勢圖	45
圖4.15利奇馬颱風（石門）搜尋之洩放量與水庫水位趨勢圖	46
圖4.16利奇馬颱風（翡翠）搜尋之洩放量與水庫水位趨勢圖	47
圖4.17(改)賀伯颱風（石門）搜尋之洩放量與水庫水位趨勢圖	48
圖4.18(改)賀伯颱風（翡翠）搜尋之洩放量與水庫水位趨勢圖	49

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