本研究針對鐵路系統之服務計畫問題，提出一套結合路線容量與編組運用考量之數學規畫模式。傳統鐵路運轉計畫通常依序進行服務計畫、排點與編組運用計畫之編擬，然而此階段性規畫方式缺乏下游資源限制考量，為後續排點或編組運用編擬工作帶來相當困難，且常需反覆調整服務計畫內容，增加作業成本。本研究以臺灣鐵路公司（臺鐵）系統為研究對象，建立混合整數線性規畫（MILP）模式，納入編組運用以及路軌所提供之容量供給與折返、停靠等操作之容量需求考量，使服務計畫能兼顧可行性與資源限制。
本模式具有相當的求解複雜度。為此本研究提出了二階段求解演算法以求得模式之最佳解。同時並提出減少雙元整數變數的策略，可在更短的時間內得到品質良好的服務計畫。本研究以小規模測試例驗證模式正確性，並以臺鐵全系統為藍圖設計大型測試例，確認可在合理時間內完成接近臺鐵真實規模問題之求解。

This study proposes a mathematical model to solve the railway service planning problem, specifically focusing on the Taiwan Railways Administration (TRA) system. While service planning, timetabling, and rolling stock scheduling are traditionally treated as sequential stages, this separation often leads to an infeasible service plan due to operational resource constraints. Moreover, this staged planning approach lacks consideration of downstream resource limitations, creating considerable difficulties for subsequent timetabling and rolling stock scheduling, and often requiring repeated revisions to the service plan, thereby increasing operational costs. This research develops a mixed-integer linear programming (MILP) model that integrates downstream considerations—such as rolling stock scheduling and track capacity—into the upstream service planning phase so that the service plan can simultaneously satisfy feasibility and resource constraints.
A two-stage algorithm is introduced to solve the problem efficiently. In addition, strategies for reducing the number of binary integer variables are proposed, enabling the derivation of high-quality service plans within a shorter computation time. This study verifies the correctness of the model through small-scale test cases and designs large-scale test cases based on the blueprint of the entire Taiwan Railways system. The results demonstrate that the model can successfully generate feasible service plans for the large-scale TRA network, balancing transport supply with operational feasibility.

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