A Bilevel Formalism for the Peer-Reviewing Problem

TL;DR

This paper introduces a novel bilevel programming model for the peer-reviewing assignment problem, balancing reviewers' effort and review quality, and proposes a heuristic to solve it efficiently.

Contribution

It is the first to model peer-review assignment with two objectives reflecting both reviewers' and editors' perspectives, providing a new approach to fairer and more efficient matching.

Findings

The model admits feasible solutions under mild conditions.

The heuristic outperforms existing methods in fairness and effort reduction.

Numerical results demonstrate competitive review quality with less reviewer effort.

Abstract

Due to the large number of submissions that more and more conferences experience, finding an automatized way to well distribute the submitted papers among reviewers has become necessary. We model the peer-reviewing matching problem as a {\it bilevel programming (BP)} formulation. Our model consists of a lower-level problem describing the reviewers' perspective and an upper-level problem describing the editors'. Every reviewer is interested in minimizing their overall effort, while the editors are interested in finding an allocation that maximizes the quality of the reviews and follows the reviewers' preferences the most. To the best of our knowledge, the proposed model is the first one that formulates the peer-reviewing matching problem by considering two objective functions, one to describe the reviewers' viewpoint and the other to describe the editors' viewpoint. We demonstrate that both the upper-level and lower-level problems are feasible and that our BP model admits a solution under mild assumptions. After studying the properties of the solutions, we propose a heuristic to solve our model and compare its performance with the relevant state-of-the-art methods. Extensive numerical results show that our approach can find fairer solutions with competitive quality and less effort from the reviewers.