Abstract
This research develops an advanced optimization framework for two-echelon electric vehicle routing problems. It tackles complex road networks, time windows, split deliveries, and battery swapping stations. By integrating optimal intermediate depot locations with efficient routing, the multi-objective model, solved using the epsilon constraints method in GAMS, addresses urban delivery challenges. The model manages larger goods volumes through split deliveries and enhances urban distribution logistics with electric vehicles, balancing sustainability and economic viability. Key features include managing electric vehicle routing limitations, ensuring timely deliveries, and optimizing split deliveries to reduce trips and congestion. The multi-objective approach minimizes travel distance, energy consumption, and costs while maximizing service levels. Strategically locating depots reduces travel distances and enhances service area coverage, improving network responsiveness. In conclusion, this research offers a holistic approach to urban logistics with electric vehicles, enhancing operational efficiency and contributing to environmental and economic goals. It provides valuable tools for decision-makers aiming to improve urban distribution networks.
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