應用人工智慧法於電動機車充電站設址問題

經濟快速發展，家庭所得增加，為追求日常生活中之便利，代步工具(汽車、機車)與日俱增，但是也造成嚴重的二氧化碳污染。並且全球暖化日益嚴重，所以21 世紀節能減碳，便成為全球重視之議題。本研究主旨在，探討以多期經費設置電動機車充電站的設址問題，也稱區位問題(Location Problem，LP)。其主要目的是在一特定區域內，使用多期數限制經費，設置一處或多處充電站，以使民眾前往最近電動機車充電站之距離更短更便利。本論文研究主要為，使用二種人工智慧啟發式演算法，其包括免疫演算法(Immune Algorithm)、基因演算法(Genetic Algorithm)找尋電動機車充電站設點位置，並以多期數經費，判定是否設站。研究以台中潭子地區為例，以在經費有限與設站期數有限條件之下於區域內搜尋最佳設站點，使其位於節點之所有民眾，距離最近充電站的最遠距離最小化，並劃分出區域內各電動機車充電站之服務範圍，本研究實驗數值結果顯示，應用免疫演算法於電動機車設站點搜尋問題之結果較優於遺傳演算法。

關鍵字

設施區位問題；電動機車；免疫演算法；基因演算法

並列摘要

The global economy grows, and the household incomes increase rapidly in recent years. To make lives more convenient, the demand of vehicles, such as automobiles and motorcycles, increases accordingly, which results in the serious pollution of carbon dioxide. As global warming worsening, cutting down the production of carbon dioxide has become a global-emphasized issue. This paper investigates the location problem of charging stations for electric scooters by multi-phase funds. Its main purpose is to minimize the distance of people and the charging stations by applying multi-phase limited funds in a specific area such that people can be more convenient to reach a charging station nearby. Two kinds of artificial intelligence algorithm, including immune algorithm(IA) and genetic algorithm(GA), are applied for finding out possible locations to set charging stations in this research; then, determine whether or not to settle them by multi-phase funds. An example of Tanzih area in Taichung is experimented. With limited funds and phases of the stations’ establishment, we try to find the best location for the charging stations by minimizing the largest distance among people in the nodes of the area and dividing the scopes of services of every charging station. Numerical results show that the applied IA can solve the location problem of charging stations of electric scooters more effectively than GA.