| 姓名 | 張嘉君(Chia-Chun Chang) | 電子郵件信箱 | E-mail 資料不公開 | |
| 畢業系所 | 營建工程系碩士班(Department and Graduate Institute of Constrction Engineering) | |||
| 畢業學位 | 碩士(Master) | 畢業時期 | 91學年第2學期 | |
| 論文名稱(中) | 應用模擬退火法求解營建工程專案多重資源排程最佳化之研究 | |||
| 論文名稱(英) | A study on multi-resource scheduling optimization using Simulated Annealing algorithm | |||
| 檔案 |
請遵守中華民國著作權法之相關規定，切勿任意重製、散佈、改作、轉貼、播送，以免觸法。 |
論文使用權限 | 校內外均一年後公開 | |
| 論文語文/頁數 | 中文/61 | |||
| 摘要(中) | 摘要 資源排程的主要目標為使所有作業項目均能適時獲得資源如期開始施作，當資源受到限制時，能夠充分有效的利用資源，使工期延誤降到最低。傳統在求解資源排程最佳化問題時，大部分仍採用傳統數學規劃模式，如此不但會造成求解效率低落外，也常常因大量且繁雜的計算過程，而降低求解的品質。有鑑於此，前人的研究均提出新的演算模式，來改善求解效率及品質。 資源排程問題為一組合最佳化問題，受限於最佳化問題的複雜性，僅有少數類型問題可以用解析方法求得最佳解，因此在無法獲得最佳解時能更有效的找出較佳的近似最佳解為本研究的目標。起源於1953年的模擬退火法則基於此種理念而生，其原理是其以隨機的方式產生設計組合之改變，並以目標函數值模擬能量函數，使其設計組合在搜尋空間中往目標函數值較低的狀態移動，但透過隨機過程，使其設計組合能在某些條件下，具有接受能往目標函數值較高處移動的機會，此種隨機過程提供模擬退火法具有跳脫局部最佳值的能力，而成為全域搜尋最佳化。 本研究即在考量資源限制的情況下，利用模擬退火法建立的演算模式，應用模擬退火法所建構之演算模式分析求解營建工程多重資源限制下排程問題，研究結果顯示模擬退火法應用於營建工程專案確實可以有效的收斂至近似最佳解甚或最佳解。 | |||
| 摘要(英) | Abstract The goal for resource scheduling is to have all of the activities get their own resources, and then the project can be completed before the established deadline. In order to reduce the delay of the project and satisfy the requirements of real world, it is necessary to make all the resource applied in the project be efficiently allocated and utilized under the condition of resources constraint. Traditionally, mathematical models of planning are employed to find the optimal solution for project scheduling under resource constrains. However, the employed models are complicated, and hung computational burdens are usually needed. It is difficult to find the analytical solution. For those problems of project scheduling under resource constrains, it is difficult to find a solution to satisfy the requirements of limited resources because of huge searching space. Therefore, how to find the best approximation instead of real one for those problems is an important research topic. In 1953, simulated annealing algorithm has been proposed. The basic idea of the simulated annealing is to establish an object function to simulate the energy condition, and finds a set of solutions from search space with modifying the object function when the energy can reach minimum. In doing so, the energy of the object function can move toward global minimum instead of local minimum condition. Therefore, with simulated annealing algorithm, it is possible to locate the best solution. The research explores the feasibility of applying simulated annealing algorithm to find a solution with considering the project scheduling under constrained resources. The research found out that employing simulated annealing algorithm could solve the multi-resource constraint problems for construction project. The research results demonstrate that applying simulated annealing algorithm do locate a reasonable approximation. Furthermore, it is possible to find out the optimal solution in search space. | |||
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