Abstract The Electric Vehicle Routing Problem (EVRP) was addressed in this investigation using a novel Artificial Rabbit Optimization (ARO) algorithm to minimize total energy consumption and enhance sustainability. The ARO algorithm demonstrates significant efficacy, adeptly navigating complex operational constraints such as finite battery capacities, fixed charging station infrastructure, and dynamic energy depletion rates. By simulating the natural foraging and survival strategies of rabbits, the optimization model successfully transcends local optima to converge upon superior solutions. The application of this methodology resulted in an optimized routing solution with a total travel distance of 383.33. This quantitative achievement manifests as a marked reduction in aggregate distance traveled and enables strategic charging schedules that curtail both energy expenditures and vehicular downtime. The successful implementation of the ARO algorithm furnishes a potent instrument for designing greener and more efficient logistics networks. The findings confirm that such optimization not only provides economic advantages through reduced electricity consumption but also plays a pivotal role in advancing the broader adoption of green transportation. By improving operational viability, this approach directly contributes to a diminished carbon footprint and fosters a future characterized by enhanced ecological stewardship.