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A Dynamic Programming Algorithm for the Online Cutting Problem with Defects and Quality Grades

机译:一种动态编程算法,缺陷和质量等级的在线切割问题

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In this article, we propose a dynamic programming based algorithm for an online glass cutting problem that arises in the glass industry. In flat glass production, a continuous ribbon of flat glass is cut into glass products of various sizes as it flows on a conveyor belt. The glass ribbon contains defects of different types based on their severity and each glass product belongs to a quality class that indicates the maximum number of defects of each type that can be tolerated. Since the location and type of defects are detected in real time using a camera, the cutting problem has to be solved online and each cutting decision is made within a few seconds. The primary goal of this cutting problem is to minimize the amount of leftover (scrap) glass resulting from the cut products. The proposed algorithm uses a look-ahead strategy to solve a static cutting problem at each iteration to determine the products to be cut within a fixed horizon length, but implements only the first one or few of these cuts per iteration. We evaluated the algorithm on a set of realistic problems reflecting the parameters of current flat glass production lines. Computational results indicate that the proposed algorithm can reduce the amount of scrap glass by an average of 26.1%.
机译:在本文中,我们提出了一种基于动态编程的基于动态规划的算法,用于玻璃行业中出现的在线玻璃切割问题。在平板玻璃生产中,随着传送带的流动,将平板玻璃的连续带切成各种尺寸的玻璃制品。玻璃带包含基于其严重性的不同类型的缺陷,每个玻璃产品属于质量等级,表示可以容忍每种类型的最大缺陷数。由于使用相机实时检测到缺陷的位置和类型,因此必须在线解决切割问题,并且在几秒钟内进行每个切割决定。这种切割问题的主要目标是最小化由切割产品产生的剩余(废料)玻璃的量。该算法使用了前瞻性策略来解决每次迭代时静态切割问题,以确定要在固定的地平线长度内切割的产品,但仅实现每次迭代的第一个或多个。我们对反映当前扁平玻璃生产线参数的一套现实问题进行了评估。计算结果表明,该算法可以将废料量减少26.1%。

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