Network Design consists of rational and clear location finding for facilities, determining capacities and choosing sources for the demand in the network, and also determining the way for sending shipments overall the network in order to satisfy the needs of customers in the lowest possible cost. For improving the overall efficiency in the supply chain network, there is an essential need for combining and unifying both of the strategic planning and operational planning, because with this implementation, there is a much more comprehensive network design, compared to the time when there is no unification of the both. One of the operational decisions that can be implemented in the model is assembly line balancing. In the literature review undertaken for this thesis, combining both of the network design and assembly line balancing is scarcely studied; also, those studies presumed only one commodity for assembly line balancing, though we already know that there is no such thing in the real world. On the other hand, we are faced with uncertainty in the model proposed in this thesis, so in order to tackle with this, and also counter the nature of uncertainty, we use and implement the robustness approach through the mathematical model. At first, the proposed model is mixed integer non-linear programming, but then, we propose the mixed integer linear programming model. By knowing the fact that network design is a strategic programming, there is a vital need to use an exact solving approach to encounter the mathematical model, because of the importance and the magnitude of the strategic decision making and its effect in the long-term. For this reason, we use the Benders Decomposition Algorithm for the proposed model in this thesis. BDA is a very efficient and useful way for solving problems in small, medium and large sizes and dimensions. At the end, we conclude that using BDA is way more efficient and handier in solving different kinds of problems than the CPLEX solver in GAMS. The number of binary variables that BDA can support, according to the size of the problem (for this thesis), small, medium and large, are 2000, 5000, and over 500000, respectively.