The Conference Paper Assignment Problem: Using Order Weighted Averages to Assign Indivisible Goods
Abstract
We propose a novel mechanism for solving the assignment problem when we have a two sided matching problem with preferences from one side (the agents/reviewers) over the other side (the objects/papers) and both sides have capacity constraints. The assignment problem is a fundamental in both computer science and economics with application in many areas including task and resource allocation. Drawing inspiration from work in multi-criteria decision making and social choice theory we use order weighted averages (OWAs), a parameterized class of mean aggregators, to propose a novel and flexible class of algorithms for the assignment problem. We show an algorithm for finding an SUM-OWA assignment in polynomial time, in contrast to the NP-hardness of finding an egalitarian assignment. We demonstrate through empirical experiments that using SUM-OWA assignments can lead to high quality and more fair assignments.
Cite
Text
Lian et al. "The Conference Paper Assignment Problem: Using Order Weighted Averages to Assign Indivisible Goods." AAAI Conference on Artificial Intelligence, 2018. doi:10.1609/AAAI.V32I1.11484Markdown
[Lian et al. "The Conference Paper Assignment Problem: Using Order Weighted Averages to Assign Indivisible Goods." AAAI Conference on Artificial Intelligence, 2018.](https://mlanthology.org/aaai/2018/lian2018aaai-conference/) doi:10.1609/AAAI.V32I1.11484BibTeX
@inproceedings{lian2018aaai-conference,
title = {{The Conference Paper Assignment Problem: Using Order Weighted Averages to Assign Indivisible Goods}},
author = {Lian, Jing Wu and Mattei, Nicholas and Noble, Renee and Walsh, Toby},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2018},
pages = {1138-1145},
doi = {10.1609/AAAI.V32I1.11484},
url = {https://mlanthology.org/aaai/2018/lian2018aaai-conference/}
}