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Improved Approximation Algorithms for Maximum Cut and Satisfiability Problems Using Semidefinite Programming Export

J. Assoc. Comput. Mach., Vol. 42 (1995), pp. 1115-1145.

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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...


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