---
title: "Combining Fairness and Optimality when Selecting and Allocating Projects"
authors:
  - "Khaled Belahcène"
  - "Vincent Mousseau"
  - "Anaëlle Wilczynski"
doi: "10.24963/ijcai.2021/6"
url: "https://ijcai.org/proceedings/2021/6"
pdf: "https://ijcai.org/proceedings/2021/0006.pdf"
venue: "Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence"
year: 2021
pages: "38-44"
track: "Main Track"
keywords:
  - "Agent-based and Multi-agent Systems: Resource Allocation"
  - "Agent-based and Multi-agent Systems: Computational Social Choice"
---

# Combining Fairness and Optimality when Selecting and Allocating Projects

Khaled Belahcène, Vincent Mousseau, Anaëlle Wilczynski

*Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence*, pages 38-44. DOI: [10.24963/ijcai.2021/6](https://doi.org/10.24963/ijcai.2021/6)

## Abstract

We consider the problem of the conjoint selection and allocation of projects to a population of agents, e.g. students are assigned papers and shall present them to their peers. The selection can be constrained either by quotas over subcategories of projects, or by the preferences of the agents themselves. We explore fairness and optimality issues and refine the analysis of the rank-maximality and popularity optimality concepts. We show that they are compatible with reasonable fairness requirements related to rank-based envy-freeness and can be adapted to select globally good projects according to the preferences of the agents.