Improved approximation of Max-Cut on graphs of bounded degree

被引:30
作者
Feige, U
Karpinski, M
Langberg, M [1 ]
机构
[1] Weizmann Inst Sci, Dept Comp Sci & Appl Math, IL-76100 Rehovot, Israel
[2] Univ Bonn, Dept Comp Sci, D-5300 Bonn, Germany
来源
JOURNAL OF ALGORITHMS-COGNITION INFORMATICS AND LOGIC | 2002年 / 43卷 / 02期
关键词
We thank Monique Laurent for commenting on an early version of our paper. The first author is the Incumbent of the Joseph and Celia Reskin Career Development Chair. This research was supported in part by a Minerva grant; and by DFG grant 673/4-1; Esprit BR grants 7079; 21726; and EC-US 030; and by the Max-Planck Research Prize;
D O I
10.1016/S0196-6774(02)00005-6
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Let alpha similar or equal to 0.87856 denote the best approximation ratio currently known for the Max-Cut problem on general graphs. We consider a semidefinite relaxation of the Max-Cut problem, round it using the random hyperplane rounding technique of Goemans and Williamson [J. ACM 42 (1995) 1115-1145], and then add a local improvement step. We show that for graphs of degree at most Delta, our algorithm achieves an approximation ratio of at least alpha + epsilon, where epsilon > 0 is a constant that depends only on Delta. Using computer assisted analysis, we show that for graphs of maximal degree 3 our algorithm obtains an approximation ratio of at least 0.921, and for 3-regular graphs the approximation ratio is at least 0.924. We note that for the semidefinite relaxation of Max-Cut used by Goemans and Williamson the integrality gap is at least 1/0.885, even for 2-regular graphs. (C) 2002 Elsevier Science (USA). All rights reserved.
引用
收藏
页码:201 / 219
页数:19
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