The research of reverse logistics is receiving much attention recently along with growing environmental and the saving concern. This paper studies an non-linear mixed integer model of big size, multi-recover product reverse supply chain. Its objective is to minimize the total cost of the reverse net. Furthermore, a improved genetic algorithm is designed for the model. Finally, the model is tested on an example for illustrating its feasibility and effectiveness.