Abstract: As a pillar industry of the national economy, the steel industry is also one of the high-energy-consuming and high-emission industries. Sintering, as the second largest energy-consuming part of steel production, accounts for about 15% of the total energy consumption of steel. Sintering process energy mainly comes from solid fuels, and the traditional sintering optimized ore-fuel ratio is usually determined by experience, which fails to achieve a dynamic balance between raw material type and sintering process combustion consumption. To address the energy balance of the sintering process, a sintering energy balance constraint is embedded on the basis of the original constraints of chemical composition, alkalinity and raw material ratios, and a sintering dosing model based on sintering energy balance is constructed and solved by a particle swarm algorithm to achieve the synergistic optimization of sintered iron ore, melt and fuel. The PSO-VIKOR sintering based optimized ore dosing model proposed in the study improves the energy utilization of the sintering process, achieves energy saving and emission reduction in the sintering process while considering the sintering cost and quality, and contributes to the low carbon and green development of sintering in steel enterprises.