2025/06/01 by Milinović, Ivan, Uroić, Leon Stjepan, Đurasević, Marko
#Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #I.2.8 #Neural and Evolutionary Computing (cs.NE)
paper · doi:10.48550/arxiv.2506.01065
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.