4.3 Article

Connectivity Graphs of Uncertainty Regions

期刊

ALGORITHMICA
卷 78, 期 3, 页码 990-1019

出版社

SPRINGER
DOI: 10.1007/s00453-016-0191-2

关键词

Uncertainty; Geometric optimization; Connectivity; Worst-case connectivity; Best-case connectivity

资金

  1. NSF [CCF 1054779, IIS 1319573]
  2. EPSRC [EP/K015680/1]
  3. NSERC Discovery Grant
  4. Fonds quebecois de la recherche sur la nature et les technologies (FQRNT)

向作者/读者索取更多资源

We study connectivity relations among points, where the precise location of each input point lies in a region of uncertainty. We distinguish two fundamental scenarios under which uncertainty arises. In the favorable Best-CaseUncertainty, each input point can be chosen from a given set to yield the best possible objective value. In the unfavorable Worst-Case Uncertainty, the input set has worst possible objective value among all possible point locations, which are uncertain due, for example, to imprecise data. We consider these notions of uncertainty for the bottleneck spanning tree problem, giving rise to the following Best-Case Connectivity with Uncertainty problem: given a family of geometric regions, choose one point per region, such that the longest edge length of an associated geometric spanning tree is minimized. We show that this problem is NP-hard even for very simple scenarios in which the regions are line segments or squares. On the other hand, we give an exact solution for the case in which there are n + k regions, where k of the regions are line segments and n of the regions are fixed points. We then give approximation algorithms for cases where the regions are either all line segments or all unit discs. We also provide approximation methods for the corresponding Worst-Case Connectivity with Uncertainty problem: Given a set of uncertainty regions, find the minimal distance r such that for any choice of points, one per region, there is a spanning tree among the points with edge length at most r.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.3
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据