@inproceedings{ef90ec5da9e643bd924349fee3d1909b,
title = "Between proportionality and diversity: Balancing district sizes under the Chamberlin-Courant rule",
abstract = "The Monroe and Chamberlin-Courant (CC) multiwinner rules proc eed by partitioning the voters into virtual districts and assigning a unique committee member to each district, so that the voters are as satisfied with the assignment as possible. The difference between Monroe and CC is that the former creates equal-sized districts, while the latter has no constraints. We generalize these rules by requiring that the largest district can be at most X times larger than the smallest one (where X is a parameter). We show that our new rules inherit worst-case computational properties from their ancestors; evaluate the rules experimentally (in particular, we provide their visualizations, analyze actual district sizes and voter satisfaction); and analyze their approximability.",
keywords = "Algorithms, Chamberlin-Courant, Diversity, Monroe, Multiwinner elections, Proportionality, Simulations",
author = "Piotr Faliszewski and Nimrod Talmon",
note = "Publisher Copyright: {\textcopyright} 2018 International Foundation for Autonomous Agents and Multiagent Systems.; 17th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2018 ; Conference date: 10-07-2018 Through 15-07-2018",
year = "2018",
month = jan,
day = "1",
language = "English",
isbn = "9781510868083",
series = "Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS",
publisher = "International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)",
pages = "14--22",
booktitle = "17th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2018",
}