Optimizing Urban Freight Delivery in an Electric Feeder Vehicle Routing Problem

This research presents an advanced approach to optimize electric vehicle (EV) routing in logistics networks. The study develops a mathematical model that incorporates different types of EVs, including trucks and motorcycles, each with distinct capacities, energy consumption rates, and service costs. The model includes energy and load transfer at joint nodes for vehicles to collaborate by sharing energy and redistributing loads, which extends their operational ranges and optimizes route feasibility. Key constraints ensure realistic energy usage, service times, and vehicle capacity considerations, while the objective function minimizes total system costs, including fixed, travel, energy, and service costs. Results show that adjusting systems capacity and service times are two crucial factors that impact the cost and feasibility of the routing network. This work contributes to developing practical, adaptable, and eco-friendly routing solutions for modern electric vehicle logistics networks.