求解同時生產一般與再生產品最佳生產批量與排程問題之研究

Abstract

傳統的經濟批量排程問題(Economic Lot Scheduling Problem) 為考量單一生產設備生產多項（一般）產品並滿足其需求的情況下，如何決定生產批量及生產排程以降低平均總成本值，其成本項包含：(1)整備成本及(2)存貨成本。本研究主要探討在單一生產設備同時生產一般產品及再生產品，在滿足所有一般產品需求及允許部分再生產品需求短缺的前提下，求解此延伸性的經濟批量排程問題，以達到最大化平均總利潤的目標。配合再生產品必須運用回收原料的特性，本研究運用時間變動批量大小方法(Time-varying Lot Sizes Approach)建構本問題的數學模式。運用基因演算法(Genetic Algorithm)搭配區域搜尋及禁忌清單的方式，本研究提出一個整合性的求解演算法。為驗證所提出之求解演算法的效能，本研究運用隨機產生的實驗數據，與共同週期法(Common Cycle Approach)所獲得之結果進行比較及分析。數據結果顯示本研究所提出之整合性求解演算法，可以有效求得比共同週期法更好的解。

The conventional Economic Lot Scheduling Problem (ELSP) considers the production lot sizing and scheduling of several products on a single facility so as to minimize the average total cost. The conventional ELSP includes the following two cost terms in its objective function, namely, setup cost and holding cost. This study invests the ELSP for the production lot sizing and scheduling of multiple regular products and remanufactured products on a single facility. The objective of this (extended) ELSP is to maximize the average total profit under the conditions of meeting the demand of all regular products, but allowing shortage for remanufactured products. Considering the recycling of remanufactured products, we formulate a mathematical model for this extended ELSP using the Time-Varying Lot Sizes (TVLS) approach. In this study, we propose an integrated solution approach that incorporates a genetic algorithm and a local search with a tabu list approach for solvomg this TVLS model. To verify the effectiveness of the proposed solution approach, we compare it with the Common Cycle (CC) approach. Our numerical experiments demonstrate that the proposed solution approach is able to solve significantly better solutions than the CC approach.