Approximation algorithms for MAX-3-CUT and other problems via complex semidefinite programming

Conference Proceedings of the Annual ACM Symposium on Theory of Computing

Volumn , Issue , 2001, Pages 443-452

  Goemans, M X ^a   Williamson, D P ^a  

^a MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; APPROXIMATION THEORY; NONLINEAR PROGRAMMING; OPTIMIZATION; POLYNOMIALS; SET THEORY; THEOREM PROVING; VECTORS;

COMBINATORIAL OPTIMIZATION; SEMIDEFINITE PROGRAMMING;

COMBINATORIAL MATHEMATICS;

EID: 0034827606     PISSN: 07349025     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/380752.380838     Document Type: Conference Paper

References (23)

1. Interior point methods in semidefinite programming with applications to combinatorial optimization
2. A new way to use semidefinite programming with applications to linear equations mod
3. A geometric approach to betweenness
4. On approximate graph colouring and MAX-k-CUT algorithms based on the ν-function
5. Linear systems in jordan algebras and primal-dual interior point algorithms
6. Approximating the value of two proper proof systems, with applications to MAX-2SAT and MAX-DICUT
7. Improved approximation algorithms for MAX k-CUT and MAX BISECTION
8. Improved approximation algorithms for maximum cut and satisfiability problems using semidefinite programming
9. The ellipsoid method and its consequences in combinatorial optimization
10. Barrier functions in interior point methods
11. Approximate graph coloring by semidefinite programming
12. On the Shannon capacity of a graph
13. Interior-point polynomial algorithms in convex programming
14. Self-scaled barriers and interior-point methods for convex programming
15. Primal-dual interior-point methods for self-scaled cones
16. Extension of commutative class of primal-dual interior point algorithms to symmetric cones
17. Associative algebras, symmetric cones and polynomial time interior point algorithms
18. Convex quadratic and semidefinite programming relaxations in scheduling
19. The Chebyshev polynomials of a matrix
20. Outward rotations: A tool for rounding solutions of semidefinite programming relaxations, with applications to MAX CUT and other problems