Optimal Route Planning and Energy Consumption Analysis of Electric Logistics Vehicles

This paper analysis the energy consumption of the traditional vehicle routing problem (VRP), which primarily focuses on minimizing distance, by proposing a more comprehensive route planning method for electric logistics vehicles (ELV). The proposed method is based on the simulated annealing (SA) algorithm and introduces energy consumption parameters to enhance the accuracy and effectiveness of the route optimization. In addition to distance, the study considers a range of factors that influence energy consumption, such as temperature, rainfall, time of day, vehicle load, slope angle, and rolling resistance. By integrating these parameters, the proposed approach transitions from a purely distance-centric model to one that mirrors real-world conditions more closely. The use of SA is crucial in this context, as it helps to avoid local optima and ensures the attainment of a global optimal solution. Moreover, the study conducts simulations by varying the weights assigned to distance and energy consumption while keeping other factors constant. These simulations demonstrate how different weight settings can impact energy consumption, enabling the identification of the most efficient route. The proposed method not only reduces time costs but also minimizes financial losses caused by uncontrollable factors, making it a significant advancement in the field of logistics and transportation.