首页> 外文会议>Annual European Symposium on Algorithms >Deeper Local Search for Better Approximation on Maximum Internal Spanning Trees
【24h】

Deeper Local Search for Better Approximation on Maximum Internal Spanning Trees

机译:深入的本地搜索最大内部跨越树的更好近似

获取原文
获取外文期刊封面目录资料

摘要

Spanning tree has been fundamental in the research of graph algorithms. In this paper, we study the optimization problem MAXIST, which maximizes the number of internal nodes in a spanning tree of a given graph, and is a generalization of the famous HAMILTONIAN-PATH problem. We present a polynomial-time approximation algorithm based on a deep local search strategy, identify combinatorial structures that support thorough analysis on the spanning trees resulted from such deep local search strategies, and prove that our algorithm has an approximation ratio 1.5 for the MAXIST problem, improving the previous best approximation algorithm of ratio 5/3 for the problem.
机译:生成树在图形算法的研究中一直是基础。在本文中,我们研究了最大化问题,最大化了给定图的生成树中的内部节点的数量,并且是着名的Hamilton-Path问题的概括。我们提出了一种基于深度本地搜索策略的多项式时间近似算法,识别支持跨越树木的彻底分析的组合结构,从而从这些深度本地搜索策略导致,并证明了我们的算法对于最大问题,我们的算法具有1.5的近似比率。提高以前的5/3比率最佳近似算法。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号