Abstarct: The present study studiy aimed to investigate the multi-objective optimization for power generation expansion via a hybrid system daynamic and mathematical programming approache in the period of 2015-2025. In this time period, considering the strategies and policies of the economic development programs, a combined decision making structure is considered for optimal power generation. In this study, a dynamic structure for simulation was first used and the model was modeled in four sub-models: capacity of power plants, market price, electricity generation and demand, and the results of this simulation as input parameters In the mathematical programming model. In the mathematical programming model, from a static point of view, the issue is addressed and finally provides an optimal result for deciding on the development of power plants. Four of the main objective functions responding to the research question are: Have: 1. Maximize production 2. Minimize costs 3. Maximize net present value 4. Minimize emissions. The optimal result of modeling for the first objective function is 332,880 MW, the second target function is 238,780 Rials per kilowatt-hour, the target's third function is 730,000, and the fourth objective function is 54,750 million tons for the horizon of 1404, and The optimal production of the power plants is from the highest to lowest levels in the solar cells of 44321, the combined cycle of 31800, the boiler 29134, the solar energy 20143, the natural gas of 7539 and the wind energy of 3700 megawatts per hour. Considering the optimal production of various types of power plants and the combination of target functions and potential of our country in the energy sector in the coming years, solar power plants have the largest share of capacity expansion and the model has the most environmental aspect. The initial data are from the energy balance sheet of the year 2014 and the Iranian power industry in 2015, and in cooperation with the Ministry of Energy.