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Near-optimal algorithms for maximum constraint satisfaction problems

Published:04 July 2009Publication History
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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(√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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    • Published in

      cover image ACM Transactions on Algorithms
      ACM Transactions on Algorithms  Volume 5, Issue 3
      July 2009
      222 pages
      ISSN:1549-6325
      EISSN:1549-6333
      DOI:10.1145/1541885
      Issue’s Table of Contents

      Copyright © 2009 ACM

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      Publication History

      • Published: 4 July 2009
      • Accepted: 1 January 2009
      • Revised: 1 December 2008
      • Received: 1 February 2007
      Published in talg Volume 5, Issue 3

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