駕駛電動車輛可大幅減少運輸部門當中溫室氣體的排放量以及石化燃料消耗量。然而現今電動車輛續航力不足，若沒有一套有效率的相關基礎設施建置方案，則推動將窒礙難行。本研究以數學規劃方法建構出數學模式，並結合本研究發展的可及路徑演算法搭配隱約式窮舉法，建構一套比流動補充站選址模式(Deviation-flow refueling location model ,DFRLM)更有效率的演算流程。
流動補充站選址模式須對最大偏航距離進行限制以降低求解複雜度，隨著車輛續航力增加或是最大偏航距離增加時，流動補充站選址模式會產生求解越來越困難的現象；而本研究所發展的可及路徑演算法則讓求解全域最佳解的時間大幅縮短，且不需事先針對偏航距離進行限制。

To drive electric vehicles(EV) would dramatically reduce greenhouse gas emissions and consumptions of fossil fuels in transportation sections. However, the vehicle range of EV is relatively short than combustion engine cars. It would be difficult to Popularize EV if we don’t establish an efficient plan for locating EV infrastructure. In our research, we develop a mathematical model by mathematical programing method. Combining with Reachable Path algorithm and Implicit Enumeration algorithm, we propose a much more efficient process than DFRLM’s to solve this location problem.
Our algorithm cost less computing time when we increasing vehicle range, whereas DFRLM costs much time. Besides, DFRLM need to put limit on deviation distance to downsize the scale of problem, otherwise, it would hardly solving the problem. On the contrary, we don’t put any limit on deviation distance, and the computing time is far less than DFRLM’s.

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網路資源
ARTC：http://www.artc.org.tw/chinese/01_testing/01_01detail.aspx?pid=4
Better Place：http://www.betterplace.com/
IEA/OECD http://www.iea.org
IPCC：http://www.ipcc.ch/
台經院產經資料庫：http://tie.tier.org.tw/index.asp
交通部統計處：http://stat.motc.gov.tw/mocdb/stmain.jsp?sys=100
國際汽車製造協會：http://www.oica.net/
經濟部能源局：http://210.69.152.10/oil102/