The fluctuations of steel demand and production variable cost influence the steel production quantity jointly. Based on the raw material price, steel demand and steel price forecasting, steel production and inventory dynamic optimi-zation model is established. Because the model relates to a variety of steel products and periods, it belongs to large-scale problems and is hard to be solved. And in order to avoid particle swarm algorithm falls into local optimum, a portfolio algorithm combined simulated annealing and particle swarm algorithm is put forward to solve the model. Through the case of steel enterprise L, the results show that the portfolio algorithm has strong convergence and widely use and the model can be used to solve the steel enterprise’s practical production problems.%考虑钢铁企业钢材生产受钢材需求和生产变动成本波动的双重影响，在预测基础上，建立钢材生产库存多期动态优化模型。由于模型涉及多种钢材及多个时段，属于大规模问题，求解困难，且为了避免粒子群算法陷入局部最优，提出采用模拟退火与粒子群组合智能算法对模型进行求解。最后通过钢铁企业L的案例，结果表明算法具有较强的收敛性和适用性，模型可用于解决钢铁企业多期生产实际问题。
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