批量方法是生產管理的最重要課題之一，但過去研究幾乎都在假定需求為確定 (deterministic) 先隨機 (stochastic) 的條件下進行，此與實務中需求數量或分配常不確知的模糊 (fuzzy) 環境並不一致。本研究針對多階無產能限制的批量問題 (MLUR) ，將五種單階批量方法WW、ICA、SM、PPA、POQ等應用到多階模糊需求的環境，發展出適用於MRP系統中的多階模糊批量方法，並以36種需求類型，2種五階產品結構、3種成本結構為例共產生216個問題求解，發現其成本績效確較一般多階批量方法為優。作者嘗試在MRP系統中考慮需求的模糊本質，使批量方法更符合實務環境，針對本研究的結果，文末並對未來繼續研究的方向，提出若干建議。

Lot-sizing is one of the most important issues in the area of production management. This study applies single-level lot-sizing method to multi-level unconstrained resources (MLUR) lot-sizing problems with fuzzy demand, so as to develop multi-level fuzzy lot-sizing method for MRP systems. This approach is different from previous researches which focus on the conditions of deterministic or stochastic demand, that are inconsistent with the fuzzy environments in practices. A comparison between the cost performances of fuzzy method and common method is made on 216 problems, which consist of 36 sets of demand, 3 sets of cost, and 2 types of five-level product structure. The results show that fuzzy method is superior to common method. Considering the nature of fuzzy demand in MRP systems, we believe our methodology fits better the practical manufacturing environments.