Burdening calculation is the important preparatory process for special aluminum smelting, which affects product quality finally. To improve production quality and burdening efficiency and reduce the costs of material and storage logistics, a burdening optimization model of special aluminum alloy is established with melting loss of chemical elements and cyclic utilization of waste products. For multi-objective and nonlinear characteristics of this model, the real code rule is designed with the amount of raw materials and charging time as decision variables, and the multi-objective algorithm based on NSGA-III is proposed to solve it with the distributed estimation strategy. The model and algorithm are verified by means of the simulation experiment with real production data. The experimental result shows that this optimization model and the proposed algorithm meets the requirements of enterprises and can solve the burdening optimization problem for special aluminum alloy. The proposed algorithm can obtain better solutions compared to NSGA-III when solving the model.