Robust optimization model to improve supply chain network ‎productivity under uncertainty

Although the importance of supply chain agility considering the necessity of speed of action, ‎response to customers, progressive changes in the market, consumers’ needs, etc. in many ‎industries is clear both scientifically and experimentally, today organizations have found that the ‎benefit from this cooperation is greater than cases performed without collaboration with relevant ‎organizations. Meanwhile, supply chain management refers to integration of all processes and ‎activities in the supply chain through improving the relations and implementing the organizational ‎processes in order to achieve competitive advantages. On the other hand, uncertainty in the ‎supply chain results in non-optimality of decisions that are made with assumption of certainty. ‎Accordingly, the main aim of this research is to provide a model for supply chain in an agile and ‎flexible state based on uncertainty variables. The method of research has been based on a ‎mathematical model, whose stages of implementation are investigated by breaking down this ‎model step-by-step. For this purpose, in the first stage and after getting familiar with the ‎intended modeling industry, solution and simulation were done. Eventually the results were ‎compared indicating that through reducing the risk-taking (increasing the protection levels), the ‎objective function which was of minimization type worsened. This study also showed that model ‎robustification is very important in order to reduce the risk of decision-making.