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  • 标题:On the Hardness of Approximating Max $k$-Cut and its Dual
  • 本地全文:下载
  • 作者:Viggo Kann ; Sanjeev Khanna ; Jens Lagergren
  • 期刊名称:Chicago Journal of Theoretical Computer Science
  • 印刷版ISSN:1073-0486
  • 出版年度:1997
  • 卷号:1997
  • 出版社:MIT Press ; University of Chicago, Department of Computer Science
  • 摘要:

    We study the Max k-Cut problem and its dual, the Min k-Partition problem. In the Min k-Partition problem, given a graph G=(V,E) and positive edge weights, we want to find an edge set of minimum weight whose removal makes G k-colorable. For the Max k-Cut problem we show that, if P&neq;NP, no polynomial time approximation algorithm can achieve a relative error better than 1/34k. It is well known that a relative error of 1/k is obtained by a naive randomized heuristic.

    For the Min k-Partition problem, we show that for k>2 and for every epsilon>0, there exists a constant alpha such that the problem cannot be approximated within alpha|V^(2-epsilon)|, even for dense graphs. Both problems are directly related to the frequency allocation problem for cellular (mobile) telephones, an application of industrial relevance

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