Designing a Robust Dynamic Network Supply Chain Model for Global Variety of Products in Uncertainty

For this purpose, in this study, modeling is designed to design a dynamic cement supply chain network to reduce post-crisis shortage. The facilities used in the model of this study are of the two types of temporary and permanent ones that are used to meet the severe demand created after the crisis. Time parameter One of the most important parameters is due to the cavitation of cement products and also the need to meet demand at specified time. In this research, this parameter is modeled in normal and post crisis situations. Disaster victims have a different preference for meeting demand. In addition to modeling this issue, alternative or similar items are also considered. Sustainable planning has been used to make sound decisions because of the demand-side sensitivity. Genetic algorithms, particle swarm optimization, and simulation refrigeration have been used to solve larger-scale models of the algorithm. According to the results, the algorithm is of better quality than the algorithms for different dimensions. Due to the importance of demand forecasting during the planning period in this study, the adaptive fuzzy neural network method is used for forecasting demand which FCM is the best known pattern recognition and adaptability algorithm.