一維裁切問題(cutting stock problems, CSP)是其中一種具代表性的最佳化問題，主要應用於鋼鐵業、紙業、紡織業等等。裁切問題主要是研究由已知尺寸的原料中，排列出最佳的裁切組合以滿足訂單需求，並且以最小耗損、最低成本為目標。
本研究依一維原料裁切問題特性建構數學模型。在模型求解方面，由於一維原料裁切問題如同大多數組合最佳化問題，當問題規模增長同時變數量亦急遽增加，因此難以直接對模式求解的方式應用在實務上的問題規模。故設計一方法求出最小耗損之裁切組合。它提供了裁切模型一可接受解，並且達到降低耗損量的目標。

One-dimensional cutting stock problem (1D-CSP) is a commonly encountered problems, which has many applications in, e.g., steel, paper and fiber industries. Cutting stock problems (CSP) involves cutting larger raw material into smaller demanded products at minimal cost and loss.
When represented as integer programming problem the large number of variables involved normally makes the result infeasible. In this paper, we will describe a method that produces cutting patterns for material to minimize the loss. According to our computational analysis, it is observed that the method provides comparable solutions.

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