Abstract: During the project design phase, accurate calculation of earthwork volumes and optimization of earthwork allocation schemes are critical for cost control. As engineering complexity increases, traditional methods often fail to achieve efficiency and cost-effectiveness. To address this issue, this study investigates the potential of ant colony optimization (ACO) in improving earthwork allocation. First, Building Information Modeling (BIM) was employed to obtain precise earthwork volume data. Subsequently, an ACO-based optimization model was developed, with minimum fuel consumption as the primary objective, to enhance both earthwork allocation and cost efficiency. Finally, a genetic algorithm (GA) was applied for secondary optimization. The results demonstrate that the hybrid ACO-GA approach significantly reduces costs compared to conventional ACO methods in earthwork allocation planning.