In many industries, manufacturers─for various reasons─have to collect products that have been used by customers. Then, depending on the status of the returned products, appropriate decisions are made to process the products. In this paper, issues such as inventory control and product planning optimization in the environment of integrated reverse logistics have been focused on. The assumed logistics network here consisted of two stages. In the first stage, returns were subject to quality inspection using the qualitative thresholds definitions, for which they were separated and sent to the appropriate lines for recovery or disposal. In the second stage, having different amounts sent to each line, a mixed integer optimization algorithm (MILP) has been proposed to lower the total cost of the network. The proposed model, considering the minimization of the costs, is of NP-Hard problem types in which the problem increases exponentially. Therefore, in this study, Genetic Algorithm has been used to solve the model.
Type of Study:
Applicable |
Subject:
Special Received: 2016/10/7 | Accepted: 2017/03/2 | Published: 2017/06/13