全球暖化現象日益嚴重，在溫室氣體中，二氧化碳對大氣溫度的增加有極大的影響。燃燒石化燃料的汽車是二氧化碳排放的大宗之一，而計程車在汽車中具有相當可觀的碳排放比率。故近年傾向發展替代燃料車種取代現有的汽車。替代燃料車的發展中，目前由電動車取得主流地位，若將計程車隊編制由一般汽油車改為電動車，可因此減少計程車的二氧化碳排放。然而，在實務考量上，計程車隊在更改編制時，很可能要經歷一段電動車與汽油車共同參與營運的過渡期，但此類營運模式尚缺乏有效率的排程方式。因此，本研究在考量混合電動計程車與一般汽油計程車之編制下，以車隊營運者之角度，發展一計程車隊營運排程模式，以輔助業者有效地進行計程車隊營運排程。 本研究模式係利用時空網路流動方式及數學規劃方法，構建計程車隊營運排程之時空網路，並定式計程車於時空中之排程，在滿足所有確定性載客需求和實務方面限制為前提下，追求最小化車隊營運成本。本模式為含額外限制之整數網路流動問題，為增進求解效率，本研究發展兩種啟發式解法以有效地求解此問題。為評估模式與演算法之實用性，本研究以台北市為例進行範例測試，並針對不同參數進行敏感度分析，結果顯示本研究提出之模式及兩種啟發式解法在實務上可有效運用，可供決策單位作為混合電動計程車與汽油計程車的車隊營運排程之參考。;Taxis, which using fossil fuels as power, produces lots of carbon dioxide (CO2) during daily operations. Under the environmental protection trend in reducing CO2 emissions, electric vehicles that powered by electricity have been valued, and the usage of electric vehicles has also been raised in general commercial fleet in recent years. If the taxi fleet use electric vehicles instead of gasoline vehicles, CO2 emissions will be enormously reduced. However, before transferring all vehicles in a taxi fleet to be purely electric vehicles, it may need to go through a transition period of a mixed use of electric vehicles and gasoline vehicles due to the high purchasing price of electric vehicles. Nowadays, domestic taxi fleet routing/scheduling in above-mentioned transition period is mainly arranged in a manual way without system optimization, making the taxi fleet routing/scheduling inefficient. To our best knowledge, no literature is found on the routing/scheduling of a taxi fleet with mixed electric vehicles and gasoline vehicles. Therefore, considering that the taxi fleet was mixed with electric vehicles and gasoline vehicles, this study developed a scheduling model of taxi fleet by utilizing the time-space network flow technique and mathematical programming method. All reserved passenger demands must be satisfied by taxi fleet, the related operating constraints are ensured. The model was aimed to minimize the total operating cost and expected to be an effective planning tool to assist the carrier in routing/scheduling. Mathematically, the model was formulated as an integer network flow problem with side constraints. This study developed two solution algorithms based on the problem properties to efficiently solve the problem. Computational result of case study were given for evaluating the performance of the proposed model and solution algorithms. Finally, conclusions and suggestions made based on the computational results were given.
