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Machine learning multi-objective optimization for time-dependent green vehicle routing problem
DOI:10.1016/j.eneco.2025.108628.png)
Abstract
En 中文
• Proposed a model to minimize fuel consumption, travel time, and distance. • Considered real-world factors like traffic variations and vehicle load. • Combined machine learning with NSGA-2 for better and faster routing. • Offered scalable solutions for energy-efficient and cost-effective logistics.
Journal
IF:
14.2
Papers:
8.3K
Citations:
5.3W
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