國家安全是依靠國軍各部隊戰力，除強化軍事訓練外，各項武器裝備的妥善更是影響戰力的關鍵 ，而現行部隊在執行保養任務時，多仰賴人力編排及經驗分配，往往難以兼顧派工的公平性與效率性，雖然原有的經驗派工模式可以如期完成部隊每週裝備保養勤務，然其中仍有其不足及不公平之處，若可將派工限制建構數學模式，求得最佳化的派工結果，可以使任務在更加公平且有效率的方式下完成。 本研究以某陸軍聯兵旅戰支連為例，透過整數規劃理論建構最佳化數學模式，並運用LINGO 20.0 軟體求得人員最佳化之排班結果，以求在滿足各項保養人力需求與休假限制下，達成人員派工及休假公平，並有效提升排班效率，後續透過敏感度分析，檢視官士兵人數、休假天數與最低保養人數之關鍵影響因素，顯示模型具備良好決策彈性，對國軍裝備保養勤務上具有相當實務應用價值，並可依單位狀況修改各項參數做為排班之參考。;National security relies on the combat capabilities of various military units. In addition to strengthening military training， the proper maintenance of weapons and equipment is a key factor affecting combat readiness. Currently， units largely depend on manual scheduling and experience-based allocation when executing maintenance tasks. This approach often makes it difficult to balance the fairness and efficiency of task assignments. Although the traditional experience-based assignment model can successfully complete weekly equipment maintenance duties on schedule， it still suffers from limitations and inequities. By formulating task assignment constraints into a mathematical model to find optimal results， tasks can be completed in a more equitable and efficient manner. Taking a Combat Support Company of an Army Combined Arms Brigade as a case study， this research constructs an optimization mathematical model based on integer programming theory. The LINGO 20.0 software is utilized to solve for the optimal personnel scheduling results. The objective is to achieve fairness in task assignment and leave allocation while satisfying various maintenance manpower requirements and leave restrictions， thereby effectively improving scheduling efficiency. Subsequently， a sensitivity analysis is conducted to examine key influential factors， including the number of officers and soldiers， leave days， and the minimum required maintenance personnel. The results indicate that the model possesses excellent decision-making flexibility and substantial practical application value for the equipment maintenance duties of the national armed forces. Furthermore， various parameters can be adjusted according to the specific conditions of different units to serve as a reference for scheduling.
