在人口數量快速成長，對於用水的需水量愈來愈大，而在水庫因日漸淤積造成有效蓄水量逐漸減少的情況下，對於如何提升現有水庫操作之效能性與效率性，達到水庫蓄水利用之最大利益，應是水庫經營管理的最重要課題。在颱洪時期是台灣地區水庫儲蓄水資源的重要時機，在此時期水庫的運轉操作除了必須保護水庫壩體結構之安全與降低壩頂溢流之風險外，對於防洪與蓄水也是防洪運轉操作的重要考量因素。
最佳化搜尋方法發展至今已有許多不同演算法應用於水庫的操作與經營管理，卻經常面臨到決策模式所求得之最佳結果與實際需求有一段差距的窘境，為了加強水庫合理操作效率，本研究以水庫防洪操作運轉辦法及其相關軟硬體設施限制來建立防洪操作運轉模式，並運用兩種不同最佳化搜尋法－簡形法（simplex method）與限制型遺傳演算法（constrained genetic algorithm）搜尋水庫最佳洩放歷程，以探討水庫合理的防洪運轉操作之決策。其中，先利用簡形法搜尋，必須先假定洩放流洪峰發生位置，方能使用此法搜尋最佳解；而遺傳演算法使用在有眾多的限制式的最佳化問題，必須先設定適當的懲罰函數以提昇限制型遺傳演算法之搜尋效能。因此，本研究以石門水庫防洪運轉操作為例，分別以簡形法與限制型遺傳演算法來搜尋洩放歷程，結果顯示兩種方法皆能有效地消減洪峰並儲存洪水，而限制型遺傳演算法所提供之洩放歷程較簡形法在實際操作上更為合理且具實用性。

Constant population growth and dramatic economic development have resulted in a tremendous demand for water resources. With the gradual decrease of the reservoir capacities, attention must focus on improving the operational effectiveness and efficiency of existing reservoirs for maximizing the beneficial use of water storage. In Taiwan, typhoon could bring abundant water resources for future use while cause downstream flood. Consequently, a real-time flood control of a reservoir should consider decreasing peak flood stage downstream and storing floodwaters for future usage. 
Various optimization strategies (techniques) have been developed for reservoir system management and operation; however, there still exists a gap between academic research and real-world implementations. To provide information for enhancing rational operating decisions, we proposed a reservoir flood operation optimization model with flood control requirements and existing operational regulations and the simplex method and Genetic Algorithm (GA) as searching engines. However, there are some requirements before using these two search methods. For simplex method, the time of release peak is assumed at the stage of after the flood peak. For genetic algorithm, since they are usually designed for finding the optimum solution to unconstrained problems, they have to be adapted to handle constraints for constrained optimization problems. Due to many constraints and flood control requirements, it is difficult to reach a feasible solution without violation of constraints. To tackle this bottleneck, the proper penalty strategy for each parameter was proposed to guide the GA searching procedure.  The two searching methods were applied to the problem of finding the optimal release and desired storage, taking the Shihmen reservoir in Taiwan as a case study. The results demonstrated that these two methods could effectively reduce flood damages and storage floodwaters after the flood operation; moreover, GA can provide an adequate and robust way for searching the rational flood operating hydrograph.

章節目錄
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研究動機與目的	1
1.2研究方法	2
二、文獻回顧	3
2.1數學規劃理論的發展	3
2.2遺傳演算法的演進	3
2.3水資源方面的應用	4
三、理論概述	7
3.1數學規劃概述	7
3.1.1 線性規劃	8
3.1.2非線性規劃	11
3.1.3動態規劃	13
3.2遺傳演算法	13
3.2.1遺傳演算法之基本架構	14
3.2.2遺傳演算法之基本元素與運算子	16
3.2.3有限制式遺傳演算法	26
3.2.4遺傳演算法之特性	30
四、研究案例	32
4.1石門水庫簡介	32
4.2水庫防洪操作	34
4.2.1防洪運轉操作規則	34
4.2.2相關水利法規	35
4.3颱風資料蒐集與分析	36
4.4水庫颱洪操作之決策模式	37
4.5簡形法	41
4.6限制型遺傳演算法	45
4.6.1運算方法及相關參數設定	45
4.6.2懲罰函數設定	46
4.6.3搜尋範圍設定	49
4.6.4結果	51
五、結論與建議	64
5.1結論	64
5.2建議	65
參考文獻	67
表目錄
表4.1石門水庫颱風資料	36
表4.2簡形法之防洪操作結果	42
表4.3遺傳演算法及相關設定參數	45
表4.4歷時40小時的颱風限制式個數	46
表4.5 限制型GA與原始之防洪操作結果比較	54
圖目錄
圖3.1 遺傳演算法演化流程圖	15
圖3.2非整數變數之二位元編碼法示意圖	17
圖3.3 實數編碼組成之範例	17
圖3.4 輪盤式選取法之示意圖	19
圖3.5 輪盤式選取法流程圖	21
圖3.6 單點交配示意圖	23
圖3.7 多點交配示意圖	23
圖3.8 字罩交配示意圖	24
圖3.9實數編碼算術交配示意圖	25
圖3.10在解空間中的可行解區與不可行解區的分布	29
圖4.1水庫防洪操作決策模式建構與搜尋演算流程圖	32
圖4.2石門水庫集水區位置圖	34
圖4.3石門水庫運轉規線示意圖	38
圖4.4洪峰發生前後階段區別示意圖	41
圖4.5珀西颱風以簡形法搜尋之洩放量與水庫水位趨勢圖	43
圖4.6賀伯颱風以簡形法搜尋之洩放量與水庫水位趨勢圖	44
圖4.7 29場颱風以遺傳演算法搜尋之洩放量趨勢圖	53
圖4.8芙安颱風以GA搜尋之洩放量與水庫水位趨勢圖	56
圖4.9畢莉颱風以GA搜尋之洩放量與水庫水位趨勢圖	57
圖4.10裘恩颱風以GA與原操作之洩放量與水庫水位趨勢圖	58
圖4.11提姆颱風以GA搜尋之洩放量與水庫水位趨勢圖	59
圖4.12賀伯颱風以GA與原操作搜尋之洩放量與水庫水位趨勢圖	60
圖4.13瑞伯颱風以GA搜尋之洩放量與水庫水位趨勢圖	61
圖4.14象神颱風以GA搜尋之洩放量與水庫水位趨勢圖	62

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