近年來城際客運業者將聯盟之觀念運用於城際運輸上，藉此提昇公司營運績效與競爭能力。然而，以往客運業者在配合策略聯盟的排班上，各家客運業者在進行策略聯盟後，僅就現行的班次表各自以人工方式進行局部的調整，未以系統最佳化方法調整其排班。另外，良好之車隊排程對城際客運業者的營運有相當大的影響，若排程不良，則將造成聯盟效益無法達到預期。因此，在既定的營運規模下，客運業者如何能在聯盟後，充分利用現有車輛資源以改善整體營運效益，則有賴完備的客運班次表及車隊排程。緣此，本研究建立數個聯盟聯合排班模式，幫助業者在聯盟後進行車隊排程及班次表的規劃，除可幫助客運業者評估聯盟的績效外，亦有助客運業者於策略聯盟過程中的談判與決策。 本研究利用網路流動技巧建構數數個聯盟排班模式，此等模式將包含多個人流與車流時空網路，用以定式旅客與車輛在時空中的流動情況。此等模式可定式為多重貨物網路流動問題，屬NP-hard問題。最後本研究以國內城際客運業者之營運資料為例，進行實例測試與分析，測試發現結果良好，顯示本研究所構建之模式應可為未來實務上進行聯盟時之參考。 Recently, inter-city bus carriers have increasingly entered into alliances with other carriers as a means of forming completely networks and gaining more efficient operations. Vehicle fleet routing and timetable setting are not only important in inter-city bus carrier operations, but are also related to alliance effects. The setting of a good timetable not only can enhance allied inter-city bus carriers’ operating performances, but can also be a useful reference for alliance decision-making. However, most of the allied bus carriers in Taiwan use a trial-and-error process for vehicle fleet routing and its scheduling formulation. They reciprocally iterate, construct and evaluate the schedule phases manually and independently, without optimization from a systemic perspective. Such an approach is neither effective nor efficient, especially when the fleet network become large, and can possibly result in an inferior feasible solution for carriers under alliance. Therefore, in this research, we developed several coordinated scheduling models by combining vehicle fleet routing and timetable setting, in order to help the allied inter-city bus carriers solve the most satisfactory vehicle fleet routes and timetables when they entered alliances. We employed network flow techniques to construct several coordinated scheduling models, including multiple passenger-flow and fleet-flow networks in order to formulate the passenger and bus fleet flows in the dimensions of time and space. The models are formulated as multiple commodity network flow problems which are characterized as NP-hard. Finally, to evaluate the models, we performed a case study using real operating data from Taiwan inter-city bus carriers. The preliminary results are good, showing that the models could be useful for inter-city bus carrier’s alliances.