As a relaxation of the clique, a k-plex of a graph is a vertex set that each vertex is not connected with at most k vertices of this set. Given an undirected graph, the Maximum k-plex Problem (MkP) aims to find its largest k-plex. Branch and bound algorithms are a type of well-studied and effective method for exact MkP solving, whose performance depends heavily on the quality of the upper bounds. In this paper, we investigate the relaxation properties of k-plex and propose an effective upper bound called Relaxed Graph color Bound (RGB) for the MkP. To describe and calculate RGB, we propose a new quasi-independent set structure that focuses on the number of conflict vertices. We combine RGB with two of the state-of-the-art branch and bound MkP algorithms, Maplex and KpLeX. Extensive experiments on real-world benchmarks, DIMACS benchmarks, and random graphs show the excellent performance of our proposed method over the state-of-the-art algorithms.
翻译:作为分解的松动, 图形的翻滚是一个顶点集, 每个顶点在最多k 顶点上都没有关联。 在未定向的图形中, 最大 kplus 问题( MkP) 的目标是寻找最大的 kplus 。 分支和约束算法是精确 MkP 解答的一种经过充分研究和有效的方法, 其性能在很大程度上取决于上界的质量。 在本文中, 我们调查 kplus 的放松特性, 并为 MkP 提出一个有效的上层约束, 叫做 Laxered 图形色斑点( RGB ) 。 为了描述和计算 RGB, 我们提出了一个新的准独立结构, 侧重于冲突顶点的数量 。 我们将 RGB 与两个最先进的分支和约束的 MkP 算法( Malops 和 KpLeX ) 结合了。 在真实世界基准、 DIMACS 基准和随机图表上显示我们所提议的方法在状态算法上的出色表现 。