Approximate graph coloring by semidefinite programming

被引:217
|
作者
Karger, D
Motwani, R
Sudan, M
机构
[1] MIT, Comp Sci Lab, Cambridge, MA 02139 USA
[2] Stanford Univ, Stanford, CA 94305 USA
关键词
approximation algorithms; chromatic number; graph coloring; NP-completeness; randomized algorithms;
D O I
10.1145/274787.274791
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
We consider the problem of coloring k-colorable graphs with the fewest possible colors. We present a randomized polynomial time algorithm that colors a 3-colorable graph on n vertices with min {O(Delta(1/3) log(1/2) Delta log n), O(n(1/4) log(1/2) n)} colors where Delta is the maximum degree of any vertex. Besides giving the best known approximation ratio in terms of n, this marks the first nontrivial approximation result as a function of the maximum degree Delta. This result can be generalized to k-colorable graphs to obtain a coloring using min {O(Delta(1-2/k) log(1/2) Delta log n), O(n(1-3/(k+1)) log(1/2) n)} colors. Our results are inspired by the recent work of Goemans and Williamson who used an algorithm for semidefinite optimization problems, which generalize linear programs, to obtain improved approximations for the MAX CUT and MAX 2-SAT problems. An intriguing outcome of our work is a duality relationship established between the value of the optimum solution to our semidefinite program and the Lovasz theta-function. We show lower bounds on the gap between the optimum solution of our semidefinite program and the actual chromatic number; by duality this also demonstrates interesting new facts about the theta-function.
引用
收藏
页码:246 / 265
页数:20
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