چكيده به لاتين
Reduction of complex products and their subsystems (CoPS) manufacturing costs is the main factor of sustainability and survival of the manufacturers of this extent. Choosing suitable CoPS suppliers can dramatically reduce these costs and increase the competitiveness of the field’s manufacturers. In view of the fact that the cost of raw materials in the complex industries, for the production processes or the purchase of components in a ready manner, forms a substantial part of the product cost.There are also three types of choices for cops makers: Purchase ready for purchase, Purchase of materials for manufacturing processes, Outsourcing. That is, the choices are not just changes in purchasing costs, but also timely delivery changes to the customer.
In this regard, in this paper, a hybrid model of data envelopment analysis-the mathematical model to select the supplier and considering timely delivery,learning and national interest in the supply chain of complex products under uncertainty is considered.In this method, the various suppliers of complex products are evaluated based on a set of economic, technical and geographical criteria. The advantage of this step is that the more appropriate suppliers are chosen, and by eliminating the inappropriate suppliers, the complexity of which is a major problem in the mathematical models is reduced.Then, in the next step, in addition to minimizing and optimizing the purchase costs and supplier quality, respectively, the Timely delivery,learning and national interest of complex products are also maximize through a robust mathematical model. To solve this kind of multi-objective function theaugmented ε-constraint method was used, which ensures the strong optimal Pareto's answers and prevents weak Pareto ones. Finally, in order to assess the impact and usefulness of the proposed method, a case study was carried out through which useful managerial outcomes were obtained.
Keywords: Complex product ssupply chain, Robust Optimization, Uncertainty, Supplier Selection, Data Envelopment Analysis, augmented ε-constraint method, Simulation method forRobust model.
