The Electric Vehicle Routing Problem (EVRP) extends the capacitated vehicle routing problem by incorporating battery constraints and charging stations, posing significant optimization challenges. This paper introduces a Trilevel Memetic Algorithm (TMA) that hierarchically optimizes customer sequences, route assignments, and charging station insertions. The method combines genetic algorithms with dynamic programming, ensuring efficient and high-quality solutions. Benchmark tests on WCCI2020 instances show competitive performance, matching best-known results for small-scale cases. While computational demands limit scalability, TMA demonstrates strong potential for sustainable logistics planning.
@article{arxiv.2506.01065,
title = {Trilevel Memetic Algorithm for the Electric Vehicle Routing Problem},
author = {Ivan Milinović and Leon Stjepan Uroić and Marko Đurasević},
journal= {arXiv preprint arXiv:2506.01065},
year = {2025}
}