隨著經濟的快速發展，也造成嚴重的二氧化碳污染，全球面臨氣候變遷異常、暖化日益嚴重的現象，因此節能減碳與趨緩地球暖化成為本世紀全世界最重視之議題。在經濟衰退、油價高漲與環保概念的趨勢下，各國積極推動公共綠色載具系統，例如：自行車共享系統和電動機車共享系統，以緩解都會區因空間有限、人口擁擠，所造成之公路交通的壅塞和汙染。然而自行車共享系統之使用率深受氣候、地形、租借站密集程度影響，不若機車快速、便捷與機動，因此使用電力驅動的電動機車共享系統，更適合成為都市區通勤接駁的綠色交通工具。
因此本研究將過去載具共享系統營運之相關研究運用在電動機車共享系統中，在已知所有租還需求發生時段、起訖站點、需求數量、電池充耗電速率、電動機車與電池建置成本等諸多條件下，來決定系統營運初期之最佳電動機車與電池交換站內電池的建置數目。並加入符合真實世界租借行為的假設，發展出一個適用於兩種能源補充設施並存的電動機車共享系統，並以起訖需求量之相對趨勢比例關係來合理分配流量的數學模式，在最小化添購車輛和電池的成本下，以滿足一定租借需求比例為衡量策略好壞之指標，在滿足顧客需求與建設成本間取得平衡，最後以粒子群演算法求解此問題，針對電動機車共享系統營運佈署策略提出更妥善的規劃。

With the huge increasing with economic development, transportation in cars and motorcycles, so does the serious pollution of carbon dioxide and global warming. Therefore carbon reduction is the main topic worldwide in this century. Due to the concept of environmental protection, economic recession and higher oil price, green transportation has aroused more and more attentions recently, 　especially by the introduction to the concept of vehicle sharing that promotes shared vehicles to conserve energy, reduce carbon emissions, and improve traffic congestions. However, for some places with bad weather or topography not so convenient for biking, electric scooters (e-scooters) may serve better than bicycles as shared vehicles, since they are as mobile as bicycles, and can move even faster with ease.
In this thesis, we focuses on hybrid public electric scooter sharing systems, a rental station consist of battery charging stations and battery exchange station, we would like to put optimal number of e-scooters and battery in battery exchange station at each rental site in the beginning of each day so that the number of satisfied Origin-Destination demands attains specified service level requirement with minimum number of e-scooters. Thereby service requirement can be achieved with minimum total cost. Based on demand proportion and rental behavior in real world, we propose a integer model to mimic the actual e-scooter traffic between rental sites. and solve it by Particle Swarm Optimization (PSO) algorithm.

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