One-dimensional cutting stock problem to minimize material waste

The one-dimensional cutting stock problem is a key issue in manufacturing, including the preparation of raw materials for production. Steel pipe manufacturing is an example of a cutting stock issue in industry, where raw material preparation requires cutting steel sheets from stock rolls to fulfill project specifications. Steel producers usually cut steel sheets from stock rolls to satisfy specific job requirements while reducing material waste. In this study, we provide a mixed integer linear programming model for addressing the one-dimensional cutting stock issue and optimizing the cutting process in order to decrease total material waste. A numerical example is presented toshow the model's ability to optimize material use and meet production demands effectively.

一维下料问题是制造业生产原材料备料环节的核心难题之一。钢管制造便是工业场景中下料问题的典型案例：其原材料备料环节需从原料卷上裁切钢板，以满足项目的规格要求。钢铁生产商通常会从原料卷上裁切钢板，以匹配特定订单需求并降低材料损耗。本研究针对一维下料问题构建了混合整数线性规划（mixed integer linear programming）模型，用于优化下料流程以降低整体材料损耗。本文通过数值算例验证了该模型可有效优化材料利用率并满足生产需求。