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Improved Approximation Algorithms for Maximum Cut and Satisfiability Problems Using Semidefinite Programming (1995)
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| Venue: | Journal of the ACM |
| Citations: | 1195 - 13 self |
BibTeX
@ARTICLE{Goemans95improvedapproximation,
author = {M. X. Goemans and D.P. Williamson},
title = {Improved Approximation Algorithms for Maximum Cut and Satisfiability Problems Using Semidefinite Programming},
journal = {Journal of the ACM},
year = {1995},
volume = {42},
pages = {1115--1145}
}
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Abstract
We present randomized approximation algorithms for the maximum cut (MAX CUT) and maximum 2-satisfiability (MAX 2SAT) problems that always deliver solutions of expected value at least .87856 times the optimal value. These algorithms use a simple and elegant technique that randomly rounds the solution to a nonlinear programming relaxation. This relaxation can be interpreted both as a semidefinite program and as an eigenvalue minimization problem. The best previously known approximation algorithms for these problems had performance guarantees of ...
