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Optimization of urea production process is important for urea production in our country, and there are wide requirements for it. Improving quality, raising output and reducing cost all need optimization of production process. So we look upon urea production process as an unknown nonlinear function in this paper, and we get BP neural network model that can be used in optimization by function approaching. Then cyclic variable method is used to optimize that model, and we prove the validity of above-mentioned method. Finally, the optimization system of urea production process is designed and realized based on above theories by software engineering method. This system needs to implement large amount of calculations, and it is applied to the problem resolving the offline optimization.