We present a thorough experimental evaluation of several crossing minimization heuristics that are based on the construction and iterative improvement of a planarization, i.e., a planar representation of a graph with crossings replaced by dummy vertices. The evaluated heuristics include variations and combinations of the well-known planarization method, the recently implemented star reinsertion method, and a new approach proposed herein: the mixed insertion method. Our experiments reveal the importance of several implementation details such as the detection of non-simple crossings (i.e., crossings between adjacent edges or multiple crossings between the same two edges). The most notable finding, however, is that the insertion of stars in a fixed embedding setting is not only significantly faster than the insertion of edges in a variable embedding setting, but also leads to solutions of higher quality.
翻译:我们根据平面化的构造和迭代改进,即用一个图的平面表示图,用假脊椎取代了交叉点,对若干跨界最小化的累赘作了彻底的实验性评价,评价的累赘性包括众所周知的平面化方法的变异和组合、最近实施的恒星再利用方法以及此处提议的新方法:混合插入方法。我们的实验揭示出若干执行细节的重要性,例如探测非简单过境点(即相邻边缘之间的交叉点或同一两边之间的多个过境点)。然而,最显著的发现是,在固定的嵌入环境中插入恒星不仅大大快于将边缘插入变量嵌入环境,而且还导致质量更高的解决办法。