# Parallel multi-objective metaheuristics for smart communications in vehicular networks

arXiv: https://arxiv.org/abs/2501.09725 · HTML: https://mlsanity.com/paper/2501.09725/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 29 references that are in the map.
- First posted on arXiv 16 Jan 2025.

## Builds on (most cited first, 1 of 1)

- [Automatic tuning of communication protocols for vehicular ad hoc networks using metaheuristics](https://mlsanity.com/paper/2501.08847/) (2025)

## Abstract (arXiv)

This article analyzes the use of two parallel multi-objective soft computing algorithms to automatically search for high-quality settings of the Ad hoc On Demand Vector routing protocol for vehicular networks. These methods are based on an evolutionary algorithm and on a swarm intelligence approach. The experimental analysis demonstrates that the configurations computed by our optimization algorithms outperform other state-of-the-art optimized ones. In turn, the computational efficiency achieved by all the parallel versions is greater than 87 %. Therefore, the line of work presented in this article represents an efficient framework to improve vehicular communications.