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Evidence record 1365 · automatically gathered

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

Contribution: This paper presents a novel two-phase algorithmic approach that decouples preference satisfaction from fairness optimization in student team formation, achieving both objectives without compromise. The method applies simulated annealing -- a core materials science technique -- to an educational challenge, demonstrating pedagogical integration of administrative processes. Background: Forming effective teams in large engineering cohorts (100+ students) requires balancing student pref

Record details

Published: 5 June 2026
Source: arXiv
Category: Research
Topics: Bias & fairness · Children & education
Retrieved: 14 July 2026

source-onlyevidence status

These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.

Same publisher byline · Shared topic: Bias & fairness

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

arXiv cs.CY · 12 August 2026

Shared topic: Bias & fairness · Shared topic: Children & education

Impacts of Histories and Models on LLM Grading: A Study in Advanced Software Engineering Courses

arXiv · 7 June 2026

Shared topic: Bias & fairness · Shared topic: Children & education

TriEval: A Resource-Efficient Pipeline for LLM Bias, Toxicity, and Truthfulness Assessment

arXiv · 2 June 2026

Shared topic: Bias & fairness · Shared topic: Children & education

What Makes a Strong Model? A Unified Spectral Analysis of Knowledge Transfer over High-dimensional Linear Regression

arXiv · 31 May 2026

Shared topic: Bias & fairness · Shared topic: Children & education

Using AI in engineering education: a balancing act, driven by clear purpose

arXiv · 15 June 2026

Shared topic: Bias & fairness · Shared topic: Children & education

Deterministic Decisions for High-Stakes AI. A Zero-Egress Pipeline with the Deployability of RAG and the Accuracy of Machine Learning

arXiv · 28 June 2026

How to cite this record

ethics.ai (5 June 2026), “Two-Phase Simulated Annealing for Equitable Team Formation: Eliminating Complaints in Large Engineering Cohorts,” evidence record 1365, https://ethics.ai/record/1365 (originally published by arXiv).

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