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  • 标题:Simultaneous Max-Cut is harder to approximate than Max-Cut
  • 本地全文:下载
  • 作者:Amey Bhangale ; Subhash Khot
  • 期刊名称:Electronic Colloquium on Computational Complexity
  • 印刷版ISSN:1433-8092
  • 出版年度:2019
  • 卷号:2019
  • 页码:1-18
  • 出版社:Universität Trier, Lehrstuhl für Theoretische Computer-Forschung
  • 摘要:

    A systematic study of simultaneous optimization of constraint satisfaction problems was initiated in [BKS15]. The simplest such problem is the simultaneous Max-Cut. [BKKST18] gave a 878 -minimum approximation algorithm for simultaneous Max-Cut which is {\em almost optimal} assuming the Unique Games Conjecture (UGC). For a single instance Max-Cut, [GW95] gave an G W -approximation algorithm where G W 87856720 which is {\em optimal} assuming the UGC.It was left open whether one can achieve an G W -minimum approximation algorithm for simultaneous Max-Cut. We answer the question by showing that there exists an absolute constant 0 1 0 − 5 such that it is NP-hard to get an ( G W − 0 ) -minimum approximation for simultaneous Max-Cut assuming the UGC.

  • 关键词:Hardness of Approximation ; Invariance Principle ; Max-Cut ; Unique Games hardness
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