宅配業轉運中心包含營業所、轉運與大客戶多種任務，又因屬性區分為月趟次與日趟次。由於外包趟次的數量直接影響營運成本，其決策為業者每月營運相當重要的課題。另外，最佳化數學模式求算之最佳解，雖然能提供良好規劃結果，然而以往未進一步分析所得最佳解的可行機率，故難以了解其於營運時之可行性。緣此，本研究考量隨機需求下，首先以兩階段隨機規劃技巧，發展一最佳趟次模式。其次，運用統計學中二項機率分配，分析趟次結果之可行性，並了解其在各隨機狀況下可行性之變異程度。最後整合前兩部分發展一整合最佳趟次與可行性模式，求得滿足業者欲達到可行機率下之趟次結果，並比較與最佳趟次決策模式之差異，以供業者在實務運用之參考。

A transshipment center for home delivery industry carries out district, transshipment, and major customer tasks. The three types of tasks are also divided into two types of trips depending on the trip attributes: monthly and daily trips. The number of outsourcing trips directly affects the operating costs, making the decision of the outsourcing plan an importation topic for carrier’s monthly operations. In addition, an optimal solution obtained from a mathematical model can be a good plan for the carrier. However, past studies did not further analyze the feasible probability of the obtained optimal solution, making its feasibility and applicability difficult to know in actual operations. Therefore, considering stochastic demands, we first use the two-stage stochastic programming technique to develop an optimal trip plan model. Then the binomial distribution in Statistics is used to analyze the feasible probability of the trip plan in order to understand its feasibility and variances for all stochastic demand scenarios. Finally, we combine the previous two parts to develop an integrated optimal trip plan and feasibility model. The results of the integrated optimal trip plan and feasibility model and optimal trip plan model are compared. The foundlings could be useful as a reference for the carrier.