<p>In supply chain (SC) optimization problems, the location, number, and capacity of facilities are considered strategic decisions. Also, medium- and short-term decisions such as assembly policy, inventory, and scheduling are considered tactical and operational decisions. This paper deals with optimizing strategic and tactical decisions in the SC, focusing on the assembly line balancing (ALB) under demand uncertainty. To this end, using a system dynamics (SD) model, the cause-and-effect model and relationships between the variables were established by determining the effective variables. Afterward, the state flow model was designed, validated, and implemented. In the last step, two scenarios and two executive policies were identified to determine which policy was more effective to implement under each scenario. The results showed that when the limitations on the automotive industry increase (Scenario 1), the best policy is to increase the number of suppliers to manage the distance among them. Besides, when the demand for diverse products increases significantly (Scenario 2) and the company must produce diverse and heterogeneous products, the best policy is to increase manpower capacity. The contributions explore how to integrate SCND and PLB, look at the factors that affect both and their overlap, consider uncertainties, and examine dynamic distribution and production networks while also developing an SD model for heterogeneous products under uncertain conditions. The findings show that managing the supply chain effectively, especially when facing environmental limitations, is crucial for improving performance, and Policy 2 provides the best strategy in this context. Finally, the optimal values for the balance of the assembly line, customer satisfaction, and customer demand are 63%, 71%, and 84%, respectively.</p> Graphical abstract <p></p>