Fair redistricting is hard

被引：7

作者：

Kueng, Richard ^{[1
]}

Mixon, Dustin G. ^{[2
]}

Villar, Soledad ^{[3
,4
]}

机构：

[1] CALTECH, Inst Quantum Informat & Matter, Pasadena, CA 91125 USA

[2] Ohio State Univ, Dept Math, 231 W 18th Ave, Columbus, OH 43210 USA

[3] NYU, Courant Inst Math Sci, New York, NY USA

[4] NYU, Ctr Data Sci, New York, NY USA

来源：

THEORETICAL COMPUTER SCIENCE | 2019年 / 791卷

关键词：

NP-hard; Computational complexity; Gerrymandering; MEASURING COMPACTNESS; MARKOV-CHAIN; PARTISAN;

D O I：

10.1016/j.tcs.2019.04.004

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Gerrymandering is a long-standing issue within the U.S. political system, and it has received scrutiny recently by the U.S. Supreme Court. In this note, we prove that deciding whether there exists a fair redistricting among legal maps is NP-hard. To make this precise, we use simplified notions of "legal" and "fair" that account for desirable traits such as geographic compactness of districts and sufficient representation of voters. The proof of our result is inspired by the work of Mahanjan, Minbhorkar and Varadarajan that proves that planar k-means is NP-hard. (C) 2019 Elsevier B.V. All rights reserved.

引用

页码：28 / 35

页数：8

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