A new linear programming model is formulated for the optimal design of dynamic systems. It is based on the multistage process, in which some outputs of one stage are the inputs to the next stage. This scheme could be used for forecasting and re-planning the dynamic models. The computational properties show that the proposed algorithm is four times faster than the well-known simplex linear programming technique. The developed algorithm is tested on real records, obtained from an economic production system.