Dynamic Two-Echelon Electric Vehicle Routing Problem with Battery Swap Stations on Real Network

This research formulates an advanced optimization framework for tackling the complex system inherent in two-echelon electric vehicle routing problems. We consider the intricacies of a complex road network, time windows, split deliveries, and battery swapping stations. By leveraging an integrated approach that determines the optimal locations for intermediate depots and establishes efficient routing, our multi-objective model, solved using the epsilon constraints method in GAMS, adeptly navigates the challenges of urban delivery networks. The model adeptly manages larger goods volumes with split deliveries and enhances urban product distribution logistics using electric vehicles within the sophisticated GAMS/CPLEX environment. This reflects a synergy between sustainability and economic viability, focusing on the utilization of electric vehicles. The results underscore the pivotal role of sophisticated mathematical modeling in improving distribution efficiency and sustainability by optimizing the complex interplay between delivery routes, depot placement, and scheduling in dynamic urban environments.