Coordinate descent heuristics for the irregular strip packing problem of rasterized shapes
针对像素表示的不规则形状条带装箱问题，提出双扫描线表示法降低复杂度，并开发交替水平垂直搜索的坐标下降启发式算法，结合计算机视觉角点检测技术减少搜索空间，在合理时间内获得高分辨率密集布局。
We consider the irregular strip packing problem of rasterized shapes, where a given set of pieces of irregular shapes represented in pixels should be placed into a rectangular container without overlap. The rasterized shapes provide simple procedures of the intersection test without any exceptional handling due to geometric issues, while they often require much memory and computational effort in high-resolution. To reduce the complexity of rasterized shapes, we propose a pair of scanlines representation called the double scanline representation that merges consecutive pixels in each row and column into strips with unit width, respectively. Based on this, we develop coordinate descent heuristics for the raster model that repeat a line search in the horizontal and vertical directions alternately, where we also introduce a corner detection technique used in computer vision to reduce the search space. Computational results for test instances show that the proposed algorithm obtains sufficiently dense layouts of rasterized shapes in high-resolution within a reasonable computation time.