緊急救災供應鏈網路設計與救災物流配送路線規劃 : 以日本機場緊急供應鏈為例

淡江大學機構典藏 > 商管學院 > 管理科學學系暨研究所 > 學位論文 > Item 987654321/94095

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题名:	緊急救災供應鏈網路設計與救災物流配送路線規劃 : 以日本機場緊急供應鏈為例
其它题名:	Emergency supply chain network design and disaster relief logistics problem : in the case of Japan airport emergency supply chain
作者:	李明軒;Li, Ming-Hsuan
贡献者:	淡江大學管理科學學系碩士班廖述賢;謝佳琳;Liao, Shu-Hsien;Hsieh, Chia-Lin
关键词:	人道救援供應鏈(或緊急供應鏈);整合性供應鏈;區位定址及路徑問題;多目標基因遺傳演算法;啟發式演算法;Humanitarian Relief Chain;Location-Routing Problem(LRP);Integrated Supply Chain Model;Multi-objective Evolutionary Algorithm;Macro Heuristic Algorithm
日期:	2013
上传时间:	2014-01-23 13:59:27 (UTC+8)
摘要:	近年來自然災害的數量及受災害影響的人迅速增加。人道供應鏈（或緊急供應鏈）的目標是迅速提供救難物資至影響的地區，盡可能減輕人類的痛苦和死亡。本研究設計救援網路分派系統為一個區位定址及路徑問題(LRP) ，並將LRP分為兩個階段，策略階段為整合供應鏈管理議題中區為定址與庫存等問題，希望決定地區救災中心(LAC)的數量及位置，包括兩個目標：緊急救難物資總供應鏈成本及災區服務回應率(同時考量成本及時間因素)，並利用階層群集分析法改善指派問題；戰術階段則是車輛路徑規劃問題，由策略階段得知LAC所負責服務的災區後，在緊急救難車輛容量及時間窗限制下決定災後環境的配送路線，此階段考慮單目標總車輛總運輸成本最小。本研究求解方法如下，策略階段將使用NAGA-II基因遺傳演算法求解所建立之多目標最佳化模型，並經由階層式群集分析法改善指派結果，以MATLAB撰寫程式求解。戰術階段則使用混合啟發式基因遺傳演算法混合2-opt方法求解所建立之目標最佳化模型，最後完成災後車輛路徑規劃任務，以C#、JOPT與MATLAB撰寫程式求解。本研究以日本為個案進行實驗，說明本研究之模型如何在現實問題中運作，最後，在災前預算限制的情況下，找出10個潛在地區救災中心的實際位置，災後以日本311大地震進行實驗，完成災後車輛路徑規劃最佳化，此研究結果可提供於決策者最適選擇方案。 The number of natural disasters and the people affected by disasters have increased over recent years. The objective of disaster response in the humanitarian relief chain is to rapidly provide relief (emergency food, water, medicine, shelter, and supplies) to areas affected, so as to minimize human suffering and death. Therefore, the design and operation of the relief chain play significant roles in achieving an effective and efficient response. In this project, we consider both facility location and vehicle routing decisions for a humanitarian relief chain (or emergency supply chain) responding to quick-onset disasters. In this study, we consider both facility location and vehicle routing decisions for a humanitarian relief chain (or emergency supply chain) responding to quick-onset disasters. We are going to design a humanitarian relief network and its distribution system. This problem can be considered as a location-routing problem (LRP) which appears as a combination of two difficult problems: the facility location problem (FLP) and the vehicle routing problem (VRP). In this work, we consider a discrete LRP with two levels: a set of potential capacitated local authority centers (LAC) and a set of ordered customers (or victims). In terms of strategic plan, we start with a strategic overview to determine the number and the set of LACs to be installed in a humanitarian relief network. In this stage, we consider facility location and inventory issues and two conflict objectives: relief chain cost and responsiveness level of emergency supplies. In addition, a cluster analysis procedure is incorporated into a sequential heuristic to enhance the facility assignment. In terms of tactic plan, we discuss a vehicle routing problem where each LAC will be responsible for some of the disaster areas determined by the former strategic plan. Every distribution route of emergency vehicles (EVs), designated to a specific LAC (starting and ending at the LAC), will be determined when a disaster is encountered. The problem is also restricted to the capacities of the vehicles and the victims’ response time (time windows) on the disaster areas. Here, we intend to minimize the vehicle routing cost in an effective and timely manner. Our two-level problem is difficult to solve by some existing optimization algorithms due to the considerable number of decision variables and constraints resulting from the integration. Therefore, in the stage of the strategic plan, we use a hybrid multi-objective evolutionary approach based on a well-known NAGA-II evolutionary algorithm to solve the proposed multi-objective model, and in the same time, we also use cluster analysis in a sequential heuristic to improve LAC assignment. We use the software of MATLAB to solve the proposed multi-objective evolutionary algorithm for the facility location problem. However, in the stage of the tactic plan,　we use a hybrid evolutionary approach based on a well-known GA evolutionary algorithm and 2-opt routes improve algorithm to solve the proposed vehicle-routing model. In this stage, C#, JOPT as well as MATLAB are used to solve this model. Finally, computational experiments are conducted to illustrate how these proposed models make effects. We use the case of Japan 311 Earthquake as a realistic case study for post-disaster scenario. The results indicate that we have chosen 10 LACs to be installed due to pre-disaster budget constraints. At the same time, the decision maker could find out optimal solutions for the post-disaster vehicle routing optimization by our proposed methodology.
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