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The demand for potato in potato snack industry has been gradually increased, but the supply of potato has hardly met such growing demand because of a limited domestic capacity of potato farming. Usually, domestic sourcing is used between June and November, and foreign sourcing from the United States or Australia is used in other periods. A foreign order should be placed prior to 1 year in order to purchase at a low price. However, it is hard to forecast domestic demand and domestic production. Hence, under such uncertainties of domestic demand and production, finding the optimal pre-order quantity is a very important issue in potato snack industry and the productivity of the company is seriously affected by its decision. This research defines the dual sourcing problem in potato snack industry and applies a stochastic programming approach to obtain an optimal pre-order quantity. We analyze five real-world cases according to the amount of domestic demand and supply. We compare the solution of the stochastic programming approach with the expected value solution. In all cases, the stochastic programming solution achieves 2% ~ 4% cost saving than the expected value solution. Its saving corresponds to about one million dollars. Furthermore, in the sensitivity analysis, we examine the change of optimal pre-order quantity and total cost when the late-order quantity increases. The result shows that as the late-order quantity increases, the optimal pre-order quantity should be increased. The contribution of this research is two fold. First, this is the first research to define the dual sourcing problem in potato snack industry using management science. In this research, it is expected to be useful for making decisions on sourcing in agricultural industry. Second, we apply the stochastic programming approach to solve this and our approach can contribute about 3% of cost saving. Although agricultural producers generally have a low operating margin, reduction of costs for raw materials will help to improve total productivity.