结合非子图同构A Bound for Non-Subgraph Isomorphism |
|
课程网址: | http://videolectures.net/gbr07_schellewald_abfns/ |
主讲教师: | Christian Schellewald |
开课单位: | 都柏林城市大学 |
开课时间: | 2007-07-04 |
课程语种: | 英语 |
中文简介: | 在本文中,我们提出了子图同构问题的新下界。这个界限可以提供证明两个图之间没有子图同构的证据。该计算基于& ndash;的SDP松弛。尽我们所知–子图同构的新组合优化公式。我们考虑只给出两个图形实例的结构的问题实例,因此我们首先处理简单的图形。该想法基于这样的事实:对于这样的问题实例,子图同构性总是导致0作为我们的组合优化问题公式的最低可能最优目标值。因此,大于0的下限表示子问题同构不存在于问题实例中的证据。但请注意,相反,负下限并不意味着必须存在子图同构,并且只表示子图同构仍然是可能的。 |
课程简介: | In this paper we propose a new lower bound to a subgraph isomorphism problem. This bound can provide a proof that no subgraph isomorphism between two graphs can be found. The computation is based on the SDP relaxation of a – to the best of our knowledge – new combinatorial optimisation formulation for subgraph isomorphism. We consider problem instances where only the structures of the two graph instances are given and therefore we deal with simple graphs in the first place. The idea is based on the fact that a subgraph isomorphism for such problem instances always leads to 0 as lowest possible optimal objective value for our combinatorial optimisation problem formulation. Therefore, a lower bound that is larger than 0 represents a proof that a subgraph isomorphism don’t exist in the problem instance. But note that conversely, a negative lower bound does not imply that a subgraph isomorphism must be present and only indicates that a subgraph isomorphism is still possible. |
关 键 词: | 子图同构; SDP松弛; 组合优化 |
课程来源: | 视频讲座网 |
最后编审: | 2020-10-22:chenxin |
阅读次数: | 82 |