For determining optimal operation policies, it is of vital importance to the structural stability of dams, besides meeting the downstream water demands during the operation period. Since water level variations in upstream dam cause changes in loadings of the dam body, ignoring factors, which are effective in the structural stability of dams, might result in cracks and instability of dams in the long term. Therefore, in the present study, a multi-objective model was developed by integrating the reservoir structure simulation model and optimization approach in order to meet water supply demands and maintain the dam structural stability. Linear static analysis of Amir Kabir dam was performed using ABAQUS 6.14.3 software to extract the structural parameters, indicating the dam structural stability. For this purpose, a dynamic artificial neural network was also used as an interfaced model to relate the results of the simulator model to those of the proposed approach. The best solution was extracted from the optimal trade-off curve, which was developed using non-dominated sorting genetic algorithm (NSGA-II) and multi-criteria decision-making methods.Results showed that the allocation to the downstream water demands was applied in the best possible way based on the stability of the dam.A comparison between the existing and optimal conditions indicated that the value of reliability and vulnerability coefficients was improved in optimal conditions in comparison with the existing conditions. According to the results, there was a 7% rise in the fuzzy stability index in optimal conditions compared to the existing conditions that indicate better performance in the optimal model. Therefore, as to consider the downstream water demands, summer was the most deficient and spring was the least deficient with the water supply of 30% and 72%, respectively. During summer, the average optimal allocation and the average demand were 20.51 MCM and 67.50 MCM, respectively. However, this seaso
