Considering the impact of fluctuating demand, stochastic lead time and prices in the raw material procurement, a
purchasing multi-period optimization model is established for minimizing the unit purchasing cost and ensuring the supply
of raw material. To reduce the difficulty of problem solving, the model is decomposed into several sub-models. An improved
particle swarm algorithm is proposed to solve the sub-models. Finally, taking a steel enterprise as an example, the results
show that the unit purchasing cost of multi-period joint optimization is lower than the single period economic batch
purchasing and the procurement strategy for stock replenishment.