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

机译:扩展局部搜索和多边形分组,以解决二维不规则条带堆积问题

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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)是将一组对象放入具有最小长度的矩形容器中的问题。对象可以是规则和不规则多边形,而容器的宽度和长度是固定的。这项研究使用改进的扩展局部搜索(ELS)和分组多边形来求解SPP。首先,根据凸包和边界框对多边形进行分组,以产生紧密结合的多边形和接近矩形的形状簇。其次,执行使用左下角算法的布局初始化,其中每组多边形放置在最左端和最底端的位置。然后,我们开始迭代ELS,通过增加/减少容器的长度来更改布局,并重新排列要适合容器的多边形的位置。使用DAGLI,DIGHE1,FU,JAKOBS2,MAO和MARQUES数据集进行的实验表明,多边形分组平均可减少多边形数量37%,使用该方法的平均容器效率为77.28%。

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