Most Classic Problems Remain NP-hard on Relative Neighborhood Graphs and their Relatives

Pascal Kunz, T. Fluschnik, R. Niedermeier, Malte Renken
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Abstract

Proximity graphs have been studied for several decades, motivated by applications in computational geometry, geography, data mining, and many other fields. However, the computational complexity of classic graph problems on proximity graphs mostly remained open. We now study 3-Colorability, Dominating Set, Feedback Vertex Set, Hamiltonian Cycle, and Independent Set on the proximity graph classes relative neighborhood graphs, Gabriel graphs, and relatively closest graphs. We prove that all of the problems remain NP-hard on these graphs, except for 3-Colorability and Hamiltonian Cycle on relatively closest graphs, where the former is trivial and the latter is left open. Moreover, for every NP-hard case we additionally show that no $2^{o(n^{1/4})}$-time algorithm exists unless the ETH fails, where n denotes the number of vertices.
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大多数经典问题仍然是相对邻域图及其近亲上的np困难问题
由于计算几何、地理、数据挖掘和许多其他领域的应用,邻近图已经被研究了几十年。然而,经典图问题在接近图上的计算复杂度大多是开放的。我们现在研究了邻近图类上的3色性、支配集、反馈顶点集、哈密顿循环和独立集。我们证明了所有的问题在这些图上仍然是np困难的,除了相对最近的图上的3-可色性和哈密顿循环,前者是平凡的,后者是开放的。此外,对于每个np困难情况,我们还表明除非ETH失败,否则不存在$2^{o(n^{1/4})}$ time算法,其中n表示顶点数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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