Optimizing the water resources operation, especially in the agricultural sector, which has the largest share in the water resources operation, is extremely important. Therefore, in this research, while introducing Whale, Gray Wolf and Crow Search Optimization Algorithms, their performance in the optimum operation of Golestan single-reservoir system Dam was evaluated with the aim of providing water demand for the downstream lands based on reliability, Reversibility, and vulnerability indices. In this optimization problem, the objective function was defined as the minimization of the total deficiency during the operation period. Meanwhile, the constraints of continuity equation, overflow, storage and reservoir release volume were applied to the objective function of the problem. Then, the results were compared with the absolute optimal value based on the nonlinear programming method obtained from GAMS software; finally, a multi-criteria decision-making model was developed to rank the optimization algorithms in terms of performance. The absolute optimal response obtained by the GAMS software based on the nonlinear programming method was 19.41. The results showed that the Gray Wolf algorithm performed better than the other algorithms in optimizing the objective function, so that the average responses in Gray Wolf, Crow Search and Whale algorithms were 92, 84 and 67% of the absolute optimal response, respectively. Furthermore, the Gray Wolf optimization algorithm performs better than the Whale and Crow Search algorithms in all parameters. In addition, the coefficient of variation of the responses obtained by the Gray Wolf algorithm is 2 and 1.43 times smaller than that in the Whale and Crow Search Algorithms, respectively. Finally, the results of the multi-criteria decision-making model showed that the gray wolf algorithm had the first rank, as compared to the other two algorithms studied in solving the problem of the optimal operation of the Golestan dam reservoir.