A New Heuristic Algorithm for Balanced Deliberation Groups

TL;DR

This paper introduces DREAM, an improved heuristic algorithm for allocating participants into balanced deliberation groups, outperforming previous methods by optimizing demographic diversity and meeting diversity.

Contribution

The paper presents DREAM, a new heuristic algorithm that enhances group allocation by balancing demographics and minimizing repeated meetings, with added user functionalities.

Findings

DREAM outperforms the LEGACY algorithm in balancing demographics.

The algorithm effectively minimizes repeated meetings over time.

User-defined importance weights allow flexible optimization.

Abstract

We here present an improved version of the Sortition Foundation's GROUPSELECT software package, which aims to repeatedly allocate participants of a deliberative process to discussion groups in a way that balances demographics in each group and maximises distinct meetings over time. Our result, DREAM, significantly outperforms the prior algorithmic approach LEGACY. We also add functionalities to the GROUPSELECT software to help the end user. The GROUPOPT algorithm utilises random shuffles and Pareto swaps to find a locally optimal solution that maximises demographic balance and minimises the number of pairwise previous meetings, with the relative importance of these two metrics defined by the user.