Abstract: Based on early supplier involvement cooperation mode， the aggregate production planning problem of iron-steel plant （core enterprises） with multi-products， multi-process， multi-downstream enterprises in the supply chain environment is researched. In order to maximize the capacity utilization rate of core enterprises and the sales profit rate of downstream enterprises conjointly， a multi-objective optimization model is established. At the same time， the process restriction of the production capacity of each process on different products， the balance principle of production and sales， the demand expectation of downstream enterprises and the profit of further processing and sales of products are considered. Based on the Pareto dominant theory， a multi-objective multi-population cooperative updating particle swarm optimization algorithm （MMCPSO） is proposed to solve the problem， the external Pareto dominant solution is used to guide the updating of the particles in the population， and the heuristic repair rules for the infeasible solutions are designed， and the unfeasible solutions are heuristically repaired by using the sales profit ranking of product from the downstream enterprises， so as to improve the algorithm performance. The simulation results show that the algorithm is feasible and effective.

Key words: aggregate production planning （APP）, early supplier involvement （ESI）, capacity optimization, sales profit rate of downstream enterprises, multi-objective optimization