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  • 标题:Global Cardinality Constraints Make Approximating Some Max-2-CSPs Harder
  • 本地全文:下载
  • 作者:Per Austrin ; Aleksa Stankovic
  • 期刊名称:LIPIcs : Leibniz International Proceedings in Informatics
  • 电子版ISSN:1868-8969
  • 出版年度:2019
  • 卷号:145
  • 页码:1-17
  • DOI:10.4230/LIPIcs.APPROX-RANDOM.2019.24
  • 出版社:Schloss Dagstuhl -- Leibniz-Zentrum fuer Informatik
  • 摘要:Assuming the Unique Games Conjecture, we show that existing approximation algorithms for some Boolean Max-2-CSPs with cardinality constraints are optimal. In particular, we prove that Max-Cut with cardinality constraints is UG-hard to approximate within ~~0.858, and that Max-2-Sat with cardinality constraints is UG-hard to approximate within ~~0.929. In both cases, the previous best hardness results were the same as the hardness of the corresponding unconstrained Max-2-CSP (~~0.878 for Max-Cut, and ~~0.940 for Max-2-Sat). The hardness for Max-2-Sat applies to monotone Max-2-Sat instances, meaning that we also obtain tight inapproximability for the Max-k-Vertex-Cover problem.
  • 关键词:Constraint satisfaction problems; global cardinality constraints; semidefinite programming; inapproximability; Unique Games Conjecture; Max-Cut; Max-
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