@article{2485,
  author = {Arman Bahari, Mohammad Taghi Taghavi Fard, Mohammad Khalilzadeh},
  title = {Designing a Reverse Supply Chain Inventory Model with Remanufacturing Process},
  journal = {Journal of Intelligent Computing},
  year = {2018},
  volume = {9},
  number = {2},
  doi = {https://doi.org/10.6025/jic/2018/9/1/43-53},
  url = {http://www.dline.info/jic/fulltext/v9n2/jicv9n2_1.pdf},
  abstract = {Sustainability has become a significant subject in most economies, causing many leading organizations to focus on product recovery and reverse logistics. However, work with quantitative models is still rare. This research is focused on inventory control in the remanufacturing process.
In the model presented in this paper, product demand can be carried out by remanufactured and new items to minimize the use
of raw materials. In this regard, the basic assumption is that the remanufactured products are as good as new products, and
the recurring items from customers can be remanufactured at a fixed rate. In this study, a method has been developed to model
the reverse supply chain variables. An approach is used for the calculation of optimum level for the new items and the
optimum level of the returned items for remanufacturing together. The major objective is to minimize the waste and gain the
competitive advantage of the cost of conversion. From among the advantages of using the method, we may refer to the
simultaneous calculation of optimized level of newly produced items, and optimized level of returning items for remanufacturing
with the aim of minimizing wastes, and achieving competitive advantage of transformation cost. From the model analysis, it
can be concluded that the cost of ordering new products, the capacity of the remanufacturing process, the final product demand, the maintenance costs of returning items inventory for remanufacturing, and the maintenance cost of new product inventory for should be at a low level.},
}