A novel approach for enhancing grid management through peak shaving and valley filling is presented by the integration of Time-of-Use (TOU) electricity pricing and Vehicle-to-Grid (V2G) technology. To explore whether this strategy can optimize the logistics costs of the transport fleet and increase the profits of logistics operations, the study introduces a multi-objective Mixed Integer Programming (MIP) model that accounts for customer demand, Electric Vehicle (EV) travel speeds, energy consumption, and charging/discharging strategies. An improved version of the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) is developed to minimize the fleet’s total distribution costs while maximizing profits from EV discharging. Numerical experiments on diverse instance types reveal that our methodologies adeptly optimize travel paths within constrained timeframes. Results indicate marked reductions in fleet distribution costs and increased profits from discharging, while also supporting electric utilities in maintaining efficient grid operations. Ultimately, the strategy of integrating TOU electricity pricing and V2G technology fosters an optimized electricity usage framework that benefits logistics companies, power utilities, and consumers, creating a synergistic relationship across the sectors.