چكيده به لاتين
In the management systems of large industrial and professional organizations, and even small manufacturing and industrial organizations, cost calculations of products are very important with regard to the costs of supplying raw materials and production, and ultimately marketing and sales as an interconnected chain. Considering a supply-to-sale chain with the ability to receive feedback from the market and its impact on production, the concept of supply chain management has arisen that the organization's macro management by optimizing chain loops will lead to overall organization improvement and will be increased the competitiveness of its products. One of the most important link of supply chains is the selection of a tailored supplier, which, even taking into account all the important and influential parameters, can still be recommended with an uncertainty. What matters in this discussion is reducing the price of the finished product by preparation and supplying the necessary components and materials through the most appropriate selection with the least risk, which, with a robust approach and taking into account uncertainties with a development model, reduces the risk of choice. The issue that is being investigated is supply chain risk management; where the costs of supplying different parts and materials from multiple suppliers in several periods should be optimized, in which case the risk of supplier selection decreases with decreasing uncertainty and then the risk of the entire continuous supply chain will be minimized through this. For this purpose, a modeling technique is used and a mixed-integral non-linear deterministic model is proposed to select the best suppliers. This model has a dynamic feature, and it is possible to examine different conditions through it, and then the uncertainties of Supply and demand are simultaneously introduced into the model, therefore, for optimization in the uncertainty conditions, the deterministic model has been transformed into an interval robust model and then evaluated. The proposed model reduces the amount of calculations to a large extent and enables the decision maker to make the best supplier selection and order allocation in order to reduce the cost of production and procurement time, and increase the quality level and ultimately, reduce the cost and the risk of uncertainty. Finally, an example is presented to prove the proposed models and its results have been analyzed.
