Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/5740
標題: 啟發式演算法於污水下水道及地下水優選問題之研究
Application of Heuristic Algorithms on sewer network and groundwater optimization problems
作者: 陳逸平
Chen, Yi-Ping
關鍵字: Scatter search
分散搜尋法
Enhanced Ant-Tabu
sewer network
groundwater management
強化螞蟻演算法
下水道管網
地下水管理
出版社: 環境工程學系所
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摘要: 在過往環工複雜優選問題的研究中,線性規劃、非線性規劃或是動態規劃等常作為主要的求解工具,但若遭遇到較為複雜的問題時,即可能造成求解品質的大幅滑落。近年來陸續有學者以啟發式演算法取代傳統的方法求解問題,並且獲得不錯的成果。因此本研究將兩種受到廣泛運用的啟發式演算法—分散搜尋法和強化螞蟻演算法運用於環工界中常見的兩種複雜優選問題─下水道管網和地下水管理的最佳化問題。 本研究主要是利用分散搜尋法和強化螞蟻演算法分別結合下水道和地下水模式,求解下水道的最小建置成本、地下水的最小復育成本以及地下水污染源和抽水源的鑑定問題,並比較評估此兩種優選技術的求解品質及穩定度。研究的結果顯示分散搜尋法和強化螞蟻演算法皆可有效的解決相關的問題,不管是在成本的最小化或是污染與抽水源鑑定的問題上,都能成功的獲得高品質的優選解。
In the past decades, linear programming, nonlinear programming and dynamic programming were often employed to solve complicated environmental engineering optimization problems. However, they were frequently trapped in local optima and failed to solve complicated and multimodal problems efficiently and effectively. Therefore, this study developed two widely used heuristic algorithms — Scatter Search (SS) and Enhanced Ant-Tabu (EAT) to solve sewer network and groundwater management optimization problems. This study integrated SS and EAT with sewer system and groundwater simulation models, and search for the minimum sewer system construction cost, the minimum groundwater remediation cost, and identification of groundwater pollution and pumping sources. The solutions obtained by SS and EAT are also compared to evaluate the optimization quality and stability of the two techniques. The results indicate that SS and EAT are both able to successfully achieve the high-quality optimization solutions.
URI: http://hdl.handle.net/11455/5740
其他識別: U0005-1108201014403600
文章連結: http://www.airitilibrary.com/Publication/alDetailedMesh1?DocID=U0005-1108201014403600
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