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Extended local search and polygon grouping for 2D irregular strip packing problem

机译:用于2D不规则条形包装问题的扩展本地搜索和多边形分组

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Strip Packing Problem (SPP) is a problem of laying a set of objects into a rectangular container with minimum length. Objects can be regular and irregular polygons, while the container has fixed width and length. This study used modified extended local search (ELS) and grouping polygon to solve the SPP. First, polygons are grouped based on convex hull and bounding box to produce tight combination of polygons and near to rectangular shape clusters. Second, layout initialization using a bottom-left algorithm is performed, in which each group of polygon is placed on the most left and bottom position. Then, we start the iterative ELS to change the layout by increasing/reducing the length of the container and rearrange the position of the polygons to be fit in the container. Experiments using DAGLI, DIGHE1, FU, JAKOBS2, MAO and MARQUES dataset showed that polygon grouping was able to reduce the number of polygons 37% on average and the average container efficiency using the proposed method was 77.28%.
机译:剥离包装问题(SPP)是将一组物体放入具有最小长度的矩形容器中的问题。物体可以是常规和不规则的多边形,而容器具有固定的宽度和长度。本研究使用修改的扩展本地搜索(ELS)和分组多边形来解决SPP。首先,基于凸壳和边界盒对多边形进行分组,以产生多边形的紧密组合,靠近矩形形状簇。其次,执行使用左下算法的布局初始化,其中每组多边形被放置在最左侧和底部位置。然后,我们开始迭代ELS通过增加/减小容器的长度来改变布局,并将多边形的位置重新排列在容器中。使用DAGLI,DIGEE1,FU,JAKOBS2,MAO和MARQUES数据集的实验表明,多边形分组能够平均减少37%的多边形数量,使用该方法的平均集装箱效率为77.28%。

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