单位圆盘图的最小团划分
Minimum clique partition in unit disk graphs
摘要：
最小团划分（MCP）问题是将给定图的顶点集划分为最小数目的团的问题。给定平面中的$n$点，相应的单位圆盘图（UDG）将这些点作为顶点，并且边连接距离至多为1的点。MCP在单位圆盘图是已知的NP-难和几个常数因子近似是已知的，包括最近的PTAS。本文提出了两种改进的单位圆盘图最小团划分的近似算法：（I）一种按时间运行的多项式时间近似算法（PTAS）$n^{O(1/\eps^2)}$。这改进了以前的PTAS与$n^{O(1/\eps^4)}$运行时间\cite{PS09}。(II)近似比为2.16的随机二次时间算法。这改进了$O(n^2)$运行时间为\cite{CFFP04}的比率3算法。
英文摘要：
The minimum clique partition (MCP) problem is that of partitioning the vertex set of a given graph into a minimum number of cliques. Given $n$ points in the plane, the corresponding unit disk graph (UDG) has these points as vertices, and edges connecting points at distance at most~1. MCP in unit disk graphs is known to be NP-hard and several constant factor approximations are known, including a recent PTAS. We present two improved approximation algorithms for minimum clique partition in unit disk graphs: (I) A polynomial time approximation scheme (PTAS) running in time $n^{O(1/\eps^2)}$. This improves on a previous PTAS with $n^{O(1/\eps^4)}$ running time \cite{PS09}. (II) A randomized quadratic-time algorithm with approximation ratio 2.16. This improves on a ratio 3 algorithm with $O(n^2)$ running time \cite{CFFP04}.
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