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  • 标题:Characterizing Demand Graphs for (Fixed-Parameter) Shallow-Light Steiner Network
  • 本地全文:下载
  • 作者:Amy Babay ; Michael Dinitz ; Zeyu Zhang
  • 期刊名称:LIPIcs : Leibniz International Proceedings in Informatics
  • 电子版ISSN:1868-8969
  • 出版年度:2018
  • 卷号:122
  • 页码:1-22
  • DOI:10.4230/LIPIcs.FSTTCS.2018.33
  • 出版社:Schloss Dagstuhl -- Leibniz-Zentrum fuer Informatik
  • 摘要:We consider the Shallow-Light Steiner Network problem from a fixed-parameter perspective. Given a graph G, a distance bound L, and p pairs of vertices (s_1,t_1),...,(s_p,t_p), the objective is to find a minimum-cost subgraph G' such that s_i and t_i have distance at most L in G' (for every i in [p]). Our main result is on the fixed-parameter tractability of this problem for parameter p. We exactly characterize the demand structures that make the problem "easy", and give FPT algorithms for those cases. In all other cases, we show that the problem is W[1]-hard. We also extend our results to handle general edge lengths and costs, precisely characterizing which demands allow for good FPT approximation algorithms and which demands remain W[1]-hard even to approximate.
  • 关键词:fixed-parameter tractable; network design; shallow-light steiner network; demand graphs
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