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Two-Phase Simulated Annealing for Equitable Team Formation: Eliminating Complaints in Large Engineering Cohorts
- Source
- arXiv — Computers and Society
- Published
- Last verified
- 12 Aug 2026
- Confidence
- High
- Evidence
- Original document retained
- Reading time
- 1 min
- Country
- International
- Relevant to
- Research & Evidence, Operations & Delivery, Technology & Data
- Topics
- airesearchoperations
Executive summary
What happened, and why should leadership care?
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 this matters
Why is this strategically important?
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
What should be noted from the evidence?
- 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.
Evidence and confidence
How far can this assessment be trusted?
High confidence. Named institution, original document retained and analysis corroborated.
Analysis is prepared editorially by Aziz Shuaib Ausi. The original publication remains the authoritative record, and executive judgement remains entirely human.
Source
Where does this originate?
Reported by arXiv — Computers and Society · International. This briefing summarises the publication for executive use; the document itself is not reproduced here.
Read the original publication