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The Ethereal
Trilevel Memetic Algorithm for the Electric Vehicle Routing Problem
June 01, 2025 ยท Declared Dead ยท ๐ arXiv.org
"No code URL or promise found in abstract"
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Authors
Ivan Milinoviฤ, Leon Stjepan Uroiฤ, Marko ฤuraseviฤ
arXiv ID
2506.01065
Category
cs.NE: Neural & Evolutionary
Cross-listed
cs.AI
Citations
0
Venue
arXiv.org
Last Checked
4 months ago
Abstract
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.
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