Roughly speaking, gerrymandering is the systematic manipulation of the boundaries of electoral districts to make a specific (political) party win as many districts as possible. While typically studied from a geographical point of view, addressing social network structures, the investigation of gerrymandering over graphs was recently initiated by Cohen-Zemach et al. [AAMAS 2018]. Settling three open questions of Ito et al. [AAMAS 2019], we classify the computational complexity of the NP-hard problem Gerrymandering over Graphs when restricted to paths and trees. Our results, which are mostly of negative nature (that is, worst-case hardness), in particular yield two complexity dichotomies for trees. For instance, the problem is polynomial-time solvable for two parties but becomes weakly NP-hard for three. Moreover, we show that the problem remains NP-hard even when the input graph is a path.
翻译:简而言之,拉皮条是系统性地操纵选区的边界,使一个特定的(政治)政党赢得尽可能多的选区。虽然通常从地理角度研究,研究社会网络结构,但最近科恩-泽马赫等人(AMAS 2018)开始调查图上的拉皮条问题。解决Ito等人的三个未决问题[AMAS 2019],我们在限制道路和树木时将NP-硬性问题的计算复杂性归类为图上拉皮条。我们的结果主要是负面的(最坏的硬性),特别是产生两种复杂的树木二分法。例如,问题在于两个政党的多时可溶性,而三个政党则变得微弱的NP硬性。此外,我们表明,即使输入图表是一条路径,问题仍然难以解决。