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  • 學位論文

考慮起訖點連接性、最短路徑及壅塞的災後路網復原計畫

Post-disaster road network recovery plans considering origin-destination connectivity, shortest path length and congestion

指導教授 : 朱致遠
共同指導教授 : 坂井勝哉(Katsuya Sakai)

摘要


災後復原問題是災難管理循環中重要的議題。在災難發生後,城際間的交通路網會被中斷,而被破壞的交通路網需以有效率的程序被恢復至原本的狀態並同時最小化社會經濟中斷所帶來的損失,然而由於有限的資源、預算、機器與人力,在復原過程中必須依序復原路網中的連結,因此有必要建立一套能夠提供有效且快速的復原順序計畫的決策方法。 本研究透過效益損失函數來決定路網中連結的重建順序,並設計了三項最佳化模型目標式:(1)最小化起訖點連接性的需求損失(2)最小化基於最短路徑的起訖點消費者剩餘損失與(3)最小化基於最短路徑的起訖點消費者剩餘損失同時考慮交通壅塞的雙層結構。為了解決這些最佳化問題,本研究引進了兩種啟發式演算法:(1)基因演算法與(2)禁忌搜尋演算法,此外,為了改善計算的效率,本研究設置了"連結大城市優先"的起始解,期望在極短時間內得到足夠好的解。對於每一項目標式,本研究先以小型模擬路網做測試後,利用Sioux Falls路網進行案例分析。結果顯示本研究提出之方法可以針對不同特性的路網,建立有效率且具彈性的災後復原計畫。

並列摘要


Post-disaster problem is an important issue in the disaster management cycle. After a disaster happens, intercity networks would be disconnected, and the destroyed transportation network needs to recover until its original condition through the efficient procedure. Simultaneously, socioeconomic disruptions should be minimized. However, due to the limited resources, budget, machine, and manpower, we must recover each road link in order during the recovery process. It is necessary to propose a decision-making method that can provide an efficient and effective recovery order plan. This research focuses on implementing the performance loss function to decide the order of reconstructing links in the network. This research designs three optimization objective functions to address the problem: (1) minimizing total origin-destination connectivity demand losses, (2) minimizing total consumer surplus losses based on the shortest path between origins and destinations, and (3) minimizing total consumer surplus losses based on the shortest path between origins and destinations considering traffic congestion between origins and destinations with bi-level structure. To solve these optimization problems, introduce two heuristic algorithms: (1) genetic algorithm and (2) tabu search algorithm. Moreover, this research sets the initial solution which connects big cities first to improve the calculation efficiency. As a result, enough good solutions can be obtained in a very short time. For each objective function, this research conducts case studies and with/without the initial solution adjustment. To verify the algorithm performances more, this research first examines a small simulated network and tests Sioux Falls network. The conclusion is that this research can provide an efficient and flexible recovery order plan for post-disaster recovery problems based on the characteristic of the network.

參考文獻


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