In Vehicular Ad Hoc Networks (VANETs), the deployment of Roadside Units (RSUs) is crucial for optimizing network performance, including communication efficiency and coverage. However, the limited number of RSUs and the associated costs require an optimal placement strategy. This study presents a genetic algorithm-based optimization model to address the challenge of RSU distribution within VANETs. By leveraging a genetic algorithm, we aim to identify near-optimal RSU locations within a predefined region, creating a robust and well-structured topology, while complying with deployment constraints. The model is validated through a simulation scenario in the main urban area of Tirana, Albania. A multi-objective optimization model is explored, considering deployment cost and coverage area, solved using the NSGA-II algorithm. The results highlight the potential of genetic algorithms in optimizing RSU distribution for improved VANET performance and efficiency.