| 研究生: |
劉效良 Liu, Shiao-Liang |
|---|---|
| 論文名稱: |
公路平面近似線形最佳化模式 Optimazation Model for Approximate Highway Horizontal Alignment |
| 指導教授: |
李宇欣
Lee, Yusin |
| 學位類別: |
碩士 Master |
| 系所名稱: |
工學院 - 土木工程學系 Department of Civil Engineering |
| 論文出版年: | 2005 |
| 畢業學年度: | 93 |
| 語文別: | 中文 |
| 論文頁數: | 104 |
| 中文關鍵詞: | 最佳化 、平面線形 、公路設計 、遺傳演繹法 、整數規畫 |
| 外文關鍵詞: | genetic algorithm, highway design, integer programming, horizontal alignment, optimization |
| 相關次數: | 點閱:65 下載:2 |
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公路幾何設計為公路設計之最基本工作,而平面線形設計為公路幾何設計中最基礎的工作。公路平面線形設計為一項極為複雜的工作,傳統上均由工程師依其知識經驗為之,往往需要耗費大量的人力、時間以及費用。為提昇設計效率以及品質,利用電腦進行自動化與最佳化設計是一重要工作。以往平面線形最佳化設計的相關文獻中,求解的方式常使用一初始線形加以改良而逐漸趨近最佳化設計的方法。良好的初始線形可使得演算效率以及求解品質大幅提昇。本研究構建一數學模式很有效率的求解良好的公路平面近似線形以做為後續演算及設計的初始線形,以及以此近似線形做為初步與細部設計中平面線形設計的參考與依據。
本研究將設計元素組成的平面線形簡化為直線段的組合,以最小化工程成本為目標,考慮規範限制、控制區域、限制區域、折線段長度、偏角量等限制。模式將折線佈設問題分為線性與非線性兩部份,採用內外兩層的分層演算法分別對線性與非線性部份進行求解。模式外層採用啟發式演算法中的基因演繹法進行非線性求解,內層以一混合整數規劃模式進行線性求解。求解時進行回合演算,內外層交替迭代求解最佳平面近似線形本研究使用C語言撰寫程式求解該模式,以線性規劃軟體CPLEX為求解核心。論文中舉出五個測試例以驗證模式之正確性以及求解效率。
由測試結果可得知,本研究所構建之模式確實可以求解出公路平面近似線形且求解效率良好。
Geometric design is one of the most fundamental components in highway design. Horizontal alignment design of highways is arguably the most fundamental component in geometric design, and is a very complicated work. In practice, highway horizontal alignments are designed by exprienced engineers manually. As a result, the work is labor, time, and budget consuming. To improve work efficiency and quality, it is important to automate and optimize. A number of papers in the literature solve for good horizontal alignments by starting with an initial solution, then improve through iterations. For this type of approach, the quality of the initial alignment can significantly affect the solution efficiency and the quality of the resulting solution. In this research we develop a model to efficiently solve for a good approximate highway horizontal alignment. The output can be used as an initail alignment for further detailed design.
Line segments are used as a surrogate for design elements in this research. The goal is to minimize construction cost. Factors considered include code requirements, control areas, restricted areas, lengths of line segments, and inflection angle. We divide the computation into two stages according to linerality. The nonlinear stage is solved with genetic algorithm, and the linear stage has a mix integer programming model solved with CPLEX as the solution engine. We then solve the problem by iterating between the two stages. Five examples are provided in the thesis to demonstrate the model.Test results indicate that the model can yield an approximate horizontal alignment correctly and efficiently.
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