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Near-optimal algorithms for maximum constraint satisfaction problems
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ACM Transactions on Algorithms (TALG) archive
Volume 5 ,  Issue 3  (July 2009) table of contents
Article No. 32  
Year of Publication: 2009
ISSN:1549-6325
Authors
Moses Charikar  Princeton University, Princeton, NJ
Konstantin Makarychev  IBM T.J. Watson Research Center, Yorktown Heights, NY
Yury Makarychev  Microsoft Research New England, Cambridge, MA
Publisher
ACM  New York, NY, USA
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ABSTRACT

In this article, we present two approximation algorithms for the maximum constraint satisfaction problem with k variables in each constraint (MAX k-CSP).

Given a (1 − ϵ) satisfiable 2CSP our first algorithm finds an assignment of variables satisfying a 1 − O(&sqrt;ϵ) fraction of all constraints. The best previously known result, due to Zwick, was 1 − O1/3).

The second algorithm finds a ck/2k approximation for the MAX k-CSP problem (where c > 0.44 is an absolute constant). This result improves the previously best known algorithm by Hast, which had an approximation guarantee of Ω(k/(2k log k)).

Both results are optimal assuming the unique games conjecture and are based on rounding natural semidefinite programming relaxations. We also believe that our algorithms and their analysis are simpler than those previously known.


REFERENCES

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Hast, G. 2005. Approximating MAX kCSP—Out-performing a random assignment with almost a linear factor. In Proceedings of ICALP, 956--968.
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Matuura, S. and Matsui, T. 2003. New approximation algorithms for MAX 2SAT and MAX DICUT. J. Oper. Res. Soc. Japan 46, 178--188.
 
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Zwick, U. 2000. Analyzing the MAX 2-SAT and MAX DI-CUT approximation algorithms of Feige and Goemans. www.cs.au.ac.il/~zwick/my-online-papers.html.

Collaborative Colleagues:
Moses Charikar: colleagues
Konstantin Makarychev: colleagues
Yury Makarychev: colleagues