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研究生:李志華
研究生(外文):Chih-Hua Lee
論文名稱:基因演算法於震災路網搶修排程問題之研究
論文名稱(外文):Genetic Algorithms for Post-Earthquake Road-Network Emergency Repairing Scheduling Problem
指導教授:黃國平黃國平引用關係
指導教授(外文):Kuo-Ping Hwang
學位類別:碩士
校院名稱:國立成功大學
系所名稱:交通管理學系碩博士班
學門:運輸服務學門
學類:運輸管理學類
論文種類:學術論文
論文出版年:2003
畢業學年度:91
語文別:中文
論文頁數:96
中文關鍵詞:模糊數排序有限資源專案排程問題基因演算法搶修路網
外文關鍵詞:resource-constrained project scheduling problemsgenetic algorithmsemergency restorationfuzzy number rankingroad network
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以地震為主之天然災害經常導致嚴重程度災損。此對於特別是在人口高度集中之地區而言,數以千計之民眾將備受影響威脅甚或為死傷,對於重要救災功能之路網與運輸系統更造成巨大之破壞。為改善緊急救援工作效率之目的,有效率地使用有限之工程資源協助路網緊急搶修工作將是首要評估指標。受制於時間以及資源品質與數量,緊急救援管理者必須決定一最適排程計畫提出時間與空間規劃以指派工程資源處理路網搶修作業。如何協助其有效評估與處理搶修工作之災損情資以提升緊急性資源排程決策品質,在在顯示此為一重要課題。
本研究為有效解決此一組合最佳化問題,遂選以基因演算法為架構乃提出兩子模式加以解決相關問題。首先,以模糊數定義方式加以考慮搶修處理時間之模糊性。於演算法設計上整合模糊數排序方法於執行流程中,期許產製一實務可行以資排程決策。其二,以有限資源排程問題角度,採取共生式進化演算法架構為求解演算法機制,有效考慮多重專案與多單位工程資源之路網搶修排程問題。本研究各以設計範例以測試所提演算法之合理性,經由數值結果顯示求解效果良好,此一演算法確實可資路網搶修排程規劃。最後,文末討論未來相關課題之可能應用。
Major earthquakes often cause a high degree of damages. Especially in highly inhabited areas, thousands of people may be affected or killed. Lifeline networks as crucial road networks and transportation systems are damaged and lead to disruptions as well. One important aspect, which helps emergency relief operations improvements after an earthquake, is the performance that crucial road networks how fast to be restored as
possible in the first few days to weeks. The quality of the relief efforts can be improved by effective use of the available technical resources. Because time, quantity and quality of the resources are limiting factors, emergency managers do have to find an optimal schedule for assigning resources in space and time to affected roads. Therefore, the need for a method of scheduling all necessary works systematically in an adequate manner will be urgent.
Scheduling problem is NP-hard in nature. Due to quality of traditional heuristics, two enetic-based solution approaches are formulated and presented to solve in this study. First, decision variable as of duration is defined in fuzzy numbers. A fuzzy number arithmetic and ranking methods are introduced into the first algorithm to help to search potential solutions. Second, based on resource-constrained project scheduling problems (RCPSP) extended to multiple projects and multiple depots considerations, a symbiotic evolutionary algorithm is presented and solved. An efficient coding method for representation on decision variables is introduced and explored. Finally, experimental studies on test networks are conducted to demonstrate the proposed algorithms. Several results from numerical experiments show its validity. It does have some advantages and applicability on emergency restoration planning of damaged road networks.
第 一 章 緒論.........................................1-1
1.1 研究背景與動機....................................1-1
1.2 研究目的..........................................1-3
1.3 研究方法..........................................1-4
1.4 研究流程與架構....................................1-5
第 二 章 國內公路災害搶修作業現況與特性................2-1
2.1 國內公路災害搶修作業情形...........................2-1
2.2 公路搶修作業處理與緊急應變程序.....................2-2
2.3 公路災害搶修作業特性...............................2-6
2.4 小結...............................................2-8
第 三 章 文獻回顧......................................3-1
3.1 維生線網路修復問題.................................3-1
3.1.1 通信電力網路災後修復問題.........................3-1
3.1.2 路網災後修復問題.................................3-3
3.2 專案排程與模糊應用之相關文獻.......................3-8
3.2.1 模糊理論簡介.....................................3-8
3.2.2 排程與模糊專案排程問題...........................3-9
3.3 相關文獻評析.......................................3-10
第 四 章 研究方法與模式架構............................4-1
4.1 問題分析............................................4-1
4.1.1 問題說明..........................................4-1
4.1.2 問題特性..........................................4-2
4.2 基本假設............................................4-5
4.3 模式說明............................................4-7
4.3.1 模式構建想法......................................4-7
4.3.2 概念性模式........................................4-9
4.3.3 模式結構分析......................................4-14
4.4 求解方法.............................................4-15
4.4.1 基因演算法理論簡介.................................4-15
4.4.2 設計理念...........................................4-16
第 五 章 RS-1-GA演算法設計與測試.........................5-1
5.1 編碼與初始群體.......................................5-1
5.1.1 編碼...............................................5-1
5.1.2 初始群體...........................................5-3
5.2 適應值函數...........................................5-4
5.2.1 適應值函數.........................................5-5
5.2.2 模糊數排序.........................................5-5
5.3 運算子...............................................5-6
5.3.1 選擇...............................................5-6
5.3.2 交配...............................................5-7
5.3.3 突變...............................................5-8
5.4 執行流程.............................................5-10
5.5 範例測試與實驗.......................................5-11
5.5.1 範例說明...........................................5-12
5.5.2 實驗設計...........................................5-13
第 六 章 RS-m-GA演算法設計與測試.........................6-1
6.1 編碼概念與SEA架構....................................6-1
6.2 RS-M -GA演算法設計...................................6-2
6.2.1 SEA架構............................................6-2
6.2.2 共生伙伴選擇與適合度評估...........................6-4
6.3 案例研究與實驗.......................................6-4
6.3.1 案例說明...........................................6-4
6.3.2 測例1..............................................6-13
6.3.3 測例2..............................................6-17
第 七 章 結論與建議......................................7-1
7.1 結論.................................................7-1
7.2 建議.................................................7-2
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