The maximum clique problem is one of the classical NP-complete problems from combinatorial optimization.
最大团问题是组合优化中的一个经典的NP -完全问题。
The maximum clique problem (MCP) is a classical graph-theoretic problem, which aims to find the maximum complete subgraph of a given graph G.
最大团问题是一个经典的图论问题，其目标是找出给定的某个图的最大完全子图。
A new algorithm for the maximum clique problem has been presented in this paper, the local enumerative algorithm based on average degree sorting.
提出了关于最大团问题的一种新思路基于平均度排序的局部枚举算法。
The main contents are organized as follows:In chapter 1, some definitions and optimization models about the maximum clique problem are introduced.
在第一章，介绍了最大团问题的有关定义和优化模型。
This problem is a generalization of the problem of finding the maximum cardinality clique of an unweighted graph.
这个问题是寻找无权图的最大团问题的推广。
Given an undirected graph with weights on the vertices, the maximum weight clique problem is to find a subset of mutually adjacent vertices (i. e., a clique) having the largest total weight.
给定顶点赋权的无向图，图的最大权团问题是寻找每个顶点都相邻的顶点子集(团)具有最大权。
The algorithm converts surface matching problem into maximum weight clique searching problem in graph theory, and the optimal point correspondence set is represented by the maximum weight clique.
根据从接收节点得到的反馈信息，提出了一个图模型来刻画基于网络编码的重传问题，并将发送节点的重传策略模型化为图中的最小团划分。
The algorithm converts surface matching problem into maximum weight clique searching problem in graph theory, and the optimal point correspondence set is represented by the maximum weight clique.
根据从接收节点得到的反馈信息，提出了一个图模型来刻画基于网络编码的重传问题，并将发送节点的重传策略模型化为图中的最小团划分。
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