The study of carbon emissions in vehicle transportation scheduling is of significant importance. It explores the problem of batched vehicle scheduling for prefabricated components under different delivery time windows, aiming to find a transportation plan that consumes the least resources and incurs the lowest cost. To achieve this, a multi-objective green transportation scheduling model is developed, with the objectives of minimizing total carbon emissions, total transportation cost, and the maximum transportation lead time. By employing the normalization and weighting method, the multi-objective problem is transformed into a single-objective problem model. An improved genetic algorithm is designed, and appropriate crossover and mutation probabilities are set to provide feasible scheduling solutions. Additionally, simulation validation using actual case and sensitivity analysis of the comprehensive objective model demonstrate the effectiveness of the algorithm and provide important decision-making references for managers in optimizing vehicle transportation scheduling.