隨著電子商務蓬勃發展，消費行為逐漸從傳統實體商店轉向線上平台，促使快速配送需求持續上升，為滿足日益多元且即時的配送需求，物流與快遞業者積極拓展服務範疇，提供如即時配送、當日送達、到府收送等多樣化服務型態。然而，隨著B2C與C2C配送需求快速成長，傳統仰賴人工經驗進行任務指派與路線規劃之方式，已難以有效因應都會區商務快遞對於配送效率與調度彈性之高度要求。 本研究以快遞業者之角度出發，針對都會區商務快遞服務之規劃問題進行探討，考量營運成本、客戶需求服務時窗與服務水準等因素，應用一般性網路流動技巧結合數學規劃方法，構建一整合車流與物流概念之時空網路模型。此模型透過縮減物流網路之層數，有效降低問題規模，並以負利潤最小化為目標，系統性地進行車輛配送路線規劃與任務指派。由於本問題屬於含額外限制之整數網路流動問題，為NP-hard問題，當問題規模擴大時，求解難度亦隨之提升，因此本研究發展一啟發式演算法，以提升大規模問題之求解效率。最後，透過範例測試與CPLEX求解結果驗證本模式之正確性與可行性，並進一步使用啟發式演算法針對關鍵參數進行敏感度分析，以分析其對求解結果之影響。本研究結果顯示，本模式與啟發式演算法表現良好，能有效降低營運成本並提升資源運用效率，期望能作為物流與快遞業者決策之參考，有效提升快遞排程效率與服務水準。 ;The rapid growth of e-commerce has changed consumer behavior from shopping at physical stores to using online platforms, increasing the demand for fast delivery services. To meet diverse and urgent delivery needs, courier companies have expanded their services by offering options such as immediate delivery, same-day delivery, and door-to-door collection and delivery. However, as B2C and C2C deliveries grow quickly, traditional methods relying mostly on manual experience to assign tasks and plan routes are no longer efficient enough to meet the high requirements for speed and flexibility in urban courier services. This study investigates the scheduling problem of business courier services in urban areas from the viewpoint of courier providers. It considers important factors such as operating costs, customer time windows, and service quality. A space-time network model is developed by combining vehicle flow and logistics concepts through mathematical programming. The goal of this model is to minimize negative profits by systematically planning vehicle routes and assigning tasks. Because the problem studied is classified as NP-hard, meaning it becomes very difficult to solve when the problem size increases, this study proposes a decomposition-based heuristic algorithm to quickly find good solutions for large-scale cases. The accuracy and practicality of the proposed model are demonstrated through examples solved using the software CPLEX. Additionally, a sensitivity analysis is conducted to understand how key parameters affect the solutions. Results indicate that the proposed model and heuristic method can effectively reduce operating costs and improve resource utilization. This research aims to help courier providers make better scheduling decisions and enhance overall service quality.
