Two-Phase Simulated Annealing for Equitable Team Formation: Eliminating Complaints in Large Engineering Cohorts

A novel two-phase algorithmic approach utilizing simulated annealing has been developed to optimize team formation in large cohorts. This method effectively balances student preferences and fairness objectives, aiming to eliminate complaints. It addresses a gap in existing tools that either prioritize fairness over preferences or vice-versa, specifically in educational settings for engineering students.

Why it matters

This research provides a solution to a common operational challenge in managing large groups, particularly where individual preferences and equitable distribution of resources or opportunities are critical. Effective team formation can significantly improve satisfaction, reduce administrative burden, and potentially enhance outcomes by fostering more cohesive and balanced groups.

Key insights

• A new two-phase algorithmic method decouples preference satisfaction from fairness optimization in team formation.
• The method employs simulated annealing, a technique from materials science, applied to an educational challenge.
• Existing team formation tools often compromise either student preferences or fairness/balance, leading to high complaint rates.
• The new approach aims to achieve both preference satisfaction and fairness without compromise, demonstrating pedagogical integration of administrative processes.
• The problem is particularly relevant for large engineering cohorts (100+ students) where balancing preferences, fairness, and diversity is complex.

Source

arXiv — Computers and Society — https://arxiv.org/abs/2606.07270