Prediction and Optimization of Storage of Mahabad Dam Reservoir Using Continuous Genetic Algorithm (CGA)

Articles in Press

Document Type : Original Article

Authors

1 Department of Agricultural Economics, University of Sistan and Baluchestan.

2 PhD in water structures, department of water science and engineering, Tabriz University, Tabriz, Iran

10.22125/iwe.2024.425782.1768

Abstract

Due to the severe water crisis in the Mahabad Dam, it is felt necessary for the continuous management of water resources, the necessity of forecasting and optimizing this dam. Planning to optimize the use of water resources is an optimization problem, which requires the use of complex, multi-variable and multi-constrained optimization methods. In this paper, a new method is proposed to predict reservoir dam storage. Continuous Genetic Algorithm (CGA) is a new method in the field of evolutionary computing that optimizes the optimal response of various problems and is applied in the Mahabad dam. This algorithm, in comparison with other algorithms, optimizes the speed of optimal response. In this research, annual optimization for Mahabad reservoir for the whole year was conducted to achieve the optimal policy using continuous genetic algorithm. The results of this research showed a minor error (2.4%) in the implementation of the algorithm. In addition, the application of continuous genetic algorithm to the annual optimization problem and its comparison with observational data suggests the very high success rate of the proposed method.

Keywords

Main Subjects

Irrigation and Water Engineering

Articles in Press, Accepted Manuscript
Available Online from 01 January 2024

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