# A Parametric, Second-Order Cone Representable Model of Fairness for Decision-Making Problems

arXiv: https://arxiv.org/abs/2412.05143 · HTML: https://mlsanity.com/paper/2412.05143/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 Dec 2024.

## Built on by (most cited first, 2 of 2)

- [AdaFair-MARL: Enforcing Adaptive Fairness Constraints in Multi-Agent Reinforcement Learning](https://mlsanity.com/paper/2511.14135/) (2025)
- [Fairness for distribution network operations and planning](https://mlsanity.com/paper/2604.27669/) (2026)

## Abstract (arXiv)

The article develops a parametric model of fairness called "varepsilon-fairness" that can be represented using a single second-order cone constraint and incorporated into existing decision-making problem formulations without impacting the complexity of solution techniques. We develop the model from the fundamental result of finite-dimensional norm equivalence in linear algebra and show that this model has a closed-form relationship to an existing metric for measuring fairness widely used in the literature. Finally, a simple case study on the optimal operation of a damaged power transmission network illustrates its effectiveness.