本研究針對多階層可維修式存貨系統問題發展演算法，此存貨系統包含總倉維修中心與多個服務站，當零件損壞時，服務站扮演服務顧客的角色，提供新的替代品給顧客，但不對損壞零件進行維修，並根據存貨政策向總倉維修中心補貨。
總倉維修中心具有補貨和維修功能，負責維修服務站送來之損壞零件。在此存貨系統中，顧客需求的間隔時間、運輸時間及維修時間皆為隨機性的變數，為高複雜性的問題。
本研究之兩階層可維修式存貨系統採用連續補貨策略(S-1, S)，將顧客等候時間當作服務績效，而顧客等候時間為顧客發現零件損壞到更換零件後的間隔時間，即和總倉和各服務站之起始存貨水準相關，並期望在最小化成本且各服務站的顧客等候時間低於門檻值下，求得各服務站和總倉維修中心最佳的訂購策略。此系統具有一個確定目標式和多條隨機限制式且擁有龐大的解空間，無法用傳統數學模式有效率的求解，此外為了更符合真實情境的隨機性，因此本研究將發展一個模擬最佳化演算法，結合樣本平均近似法(Sample Average Approximation)、切面法(Cutting Plane Method)、可行性檢查程序(Feasible Check Procedure)和可行方向法(Feasible Direction Methods)求解問題。

We address a two-echelon spare parts repairable inventory system consisting of a central repair warehouse and some regional depots. The objective is to determine an (S-1, S) pair that minimizes a cost function, defined only in terms of holding costs, subject to the constraint that the average response time to each customer is below a threshold level. To avoid the mistakes resulting from the approximation and implausible assumptions in traditional methods, we propose an algorithm based on simulation instead of queueing theory. The R&S procedure can be used to solve simulation optimization problems for which the number of feasible solution is small, and thus we propose a simulation algorithm which combines the cutting plane method, the feasible check procedure and the feasible direction approach.

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