Abstarct: Given the growing importance of coal in human life and needs today, production in coal mines is very important. Therefore, production planning and optimization are also important. In this study methods for modeling the production program and optimizing it at the entrance of the coal washing plant in have been investigated. Using 573 input data sets in one year of coal plant operation, considering the factors affecting modeling and modeling efficiency optimization with the help of fuzzy neural network and genetic optimization algorithm production schedule completed. In this path, linear and nonlinear regression models were used, which according to the model evaluation, the models were rejected and then modeling was done using neural network and fuzzy neural network and fuzzy neural network model. It had a 9% better response than the neural network. Then, after selecting this model, optimization was performed by genetic algorithm and particle swarm algorithm, and between the two algorithms, genetic optimization algorithm was selected to optimize the model made by fuzzy neural network. Finally, modeling was performed using fuzzy neural network and genetic algorithm. Then, a proposed production plan was presented for each month of the year for the Eastern Alborz coal mines, the production of which was calculated separately by the correlation of the mines in the relevant tables separately. By applying the optimized proposed program to the current production routine, about seven percent will be added to the production efficiency in the total year with the same production conditions.