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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. We then show how to derandomize the algorithm to... (Update)
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BibTeX entry: (Update)
M.X. GOEMANS and D.P. WILLIAMSON. Improved approximation algorithms for maximum cut and satisfiability problems using semidefinite programming. Journal of Association for Computing Machinery, 42(6):1115--1145, 1995. http://citeseer.ist.psu.edu/article/goemans95improved.html More
@article{ goemans95improved,
author = "Michel X. Goemans and David P. Williamson",
title = "{Improved Approximation Algorithms for Maximum Cut and Satisfiability Problems Using Semidefinite Programming}",
journal = "{J. Assoc. Comput. Mach.}",
volume = "42",
pages = "1115--1145",
year = "1995",
url = "citeseer.ist.psu.edu/article/goemans95improved.html" }
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