# Promoting Two-sided Fairness in Dynamic Vehicle Routing Problem

arXiv: https://arxiv.org/abs/2405.19184 · HTML: https://mlsanity.com/paper/2405.19184/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 7 of its 54 references that are in the map.
- First posted on arXiv 29 May 2024.

## Builds on (most cited first, 7 of 7)

- [FairRec: Fairness-aware News Recommendation with Decomposed Adversarial Learning](https://mlsanity.com/paper/2006.16742/) (2020)
- [Balancing the Tradeoff between Profit and Fairness in Rideshare Platforms During High-Demand Hours](https://mlsanity.com/paper/1912.08388/) (2019)
- [Data-Driven Methods for Balancing Fairness and Efficiency in Ride-Pooling](https://mlsanity.com/paper/2110.03524/) (2021)
- [Almost Envy-free Repeated Matching in Two-sided Markets](https://mlsanity.com/paper/2009.09336/) (2020)
- [FairFoody: Bringing in Fairness in Food Delivery](https://mlsanity.com/paper/2203.08849/) (2022)
- [Approximating Optimisation Solutions for Travelling Officer Problem with Customised Deep Learning Network](https://mlsanity.com/paper/1903.03348/) (2019)
- [A Dynamic Tree Algorithm for Peer-to-Peer Ride-sharing Matching](https://mlsanity.com/paper/2105.13078/) (2021)

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

- [FairDRL-ST: Disentangled Representation Learning for Fair Spatio-Temporal Mobility Prediction](https://mlsanity.com/paper/2508.07518/) (2025)
- [Long-term Fairness in Ride-Hailing Platform](https://mlsanity.com/paper/2407.17839/) (2024)

## Abstract (arXiv)

Dynamic Vehicle Routing Problem (DVRP), is an extension of the classic Vehicle Routing Problem (VRP), which is a fundamental problem in logistics and transportation. Typically, DVRPs involve two stakeholders: service providers that deliver services to customers and customers who raise requests from different locations. Many real-world applications can be formulated as DVRP such as ridesharing and non-compliance capture. Apart from original objectives like optimising total utility or efficiency, DVRP should also consider fairness for all parties. Unfairness can induce service providers and customers to give up on the systems, leading to negative financial and social impacts. However, most existing DVRP-related applications focus on improving fairness from a single side, and there have been few works considering two-sided fairness and utility optimisation concurrently. To this end, we propose a novel framework, a Two-sided Fairness-aware Genetic Algorithm (named 2FairGA), which expands the genetic algorithm from the original objective solely focusing on utility to multi-objectives that incorporate two-sided fairness. Subsequently, the impact of injecting two fairness definitions into the utility-focused model and the correlation between any pair of the three objectives are explored. Extensive experiments demonstrate the superiority of our proposed framework compared to the state-of-the-art.