In many industries, manufacturers for various reasons, have to collect products are used by customers. Then, depending on the situation returns, required to process the decision taken on the product. In this paper the problem of optimizing inventory control and product planning in the environment has been integrated reverse logistics. Logistics network to consist of two stages. In the first stage returns using the qualitative thresholds defined, separated and sent to the appropriate lines recovery or disposal, are subject to quality inspection. In the second stage having different amounts sent to the line, a mixed integer optimization algorithm (MILP) to lower the total cost of our network. Model with a view to minimizing the costs, the type of problems that are NP-Hard, the problem increases exponentially. Therefore, in this study, GENETIC Algorithm is used to solve the model.