Presentation of a Method Based on Gray Wolf Optimizer and Imperialist Competitive Algorithms in Optimal Operation of Dam Reservoir

In recent decades, the optimal use of dam reservoirs among water resource management researchers has been of great interest. So, due to the high performance and capabilities of evolutionary algorithms, in this study, using gray wolf optimizer algorithm (GWO) to predict Urmia Shaharchay dam reservoir and present a short-term forecast program for next years. The gray wolf algorithm imitates the hierarchy of leadership and the mechanism of hunting gray wolves in nature. In this algorithm, four types of gray wolves consists of alpha, beta, delta and omega have been used to simulate the hierarchy of leadership. In this study, considering the annual planning and monthly intervals, GWO algorithm was firstly evaluated for prediction storage of Urmia shaharchay reservoir during 2006-202014 years and the results compared with ICA algorithm. The results showed that GWO algorithm, with a high accuracy of 90%, provides better results in finding optimal response, convergence rate and lower computational cost compared to ICA algorithm. The results of this study indicated that GWO algorithm, an appropriate algorithm to solve the optimal operation of dam reservoir system problem.