Document Type : Original Article


1 Assistant Professor of Agricultural Economics, University of Sistan and Baluchestan, Iran

2 Ph.D. Candidate of Water Engineering, Tabriz University, Iran


Water scarcity, especially in Iran and during the recent droughts, emphasizes the importance of achieving an optimal operation policy for large dam reservoirs. In the last two decades, the annual optimization of dam reservoirs under controlled conditions, as well as climatic and real conditions, has attracted many researchers and experts. This study proposes a new approach to predict reservoir dam storage. The imperialist competitive algorithm (ICA) is a new approach in the field of evolutionary computation that calculates an optimal solution for different optimization problems. Using mathematical modeling of the social-psychological evolution process, ICA provides a new approach to solve mathematical optimization problems, and compared to other algorithms, it has appropriate speed and high convergence rate in finding an optimal answer. This research used the ICA for the annual optimization of the Kahir reservoir to derive optimal policies. Objective function downstream water issue needs to establish relationships based on continuity were selected. Comparison of ICA model in population 100 showed that the ICA algorithm with average best objective function value of 125, 114.6, and 85.60 with a number of further evaluations of the objective function to achieve higher capacity is the optimum answer. The results showed a 6.1 percent error in the implementation of the ICA algorithm between the observed and predicted storages. The results of applying the ICA to the annual optimization problem demonstrate the capability of the proposed method.

Graphical Abstract

An Imperialist Competitive Algorithm (ICA)-Based Approach to Optimize the Reservoir Storage of the Kahir Dam


  • Presentation of an Imperialist Competitive Algorithm in water management.
  • Application of ICA algorithm in a drought-prone area.
  • Using socio-political indicators in water resources management.


Main Subjects

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